Tootfinder

HCOMC: A Hierarchical Cooperative On-Ramp Merging Control Framework in Mixed Traffic Environment on Two-Lane Highways
Tianyi Wang, Yangyang Wang, Jie Pan, Junfeng Jiao, Christian Claudel
https://arxiv.org/abs/2507.11621

HCOMC: A Hierarchical Cooperative On-Ramp Merging Control Framework in Mixed Traffic Environment on Two-Lane Highways
Highway on-ramp merging areas are common bottlenecks to traffic congestion and accidents. Currently, a cooperative control strategy based on connected and automated vehicles (CAVs) is a fundamental solution to this problem. While CAVs are not fully widespread, it is necessary to propose a hierarchical cooperative on-ramp merging control (HCOMC) framework for heterogeneous traffic flow on two-lane highways to address this gap. This paper extends longitudinal car-following models based on the int…

Dynamic Scheduling for Enhanced Performance in RIS-assisted Cooperative Network with Interference
Yomali Lokugama, Saman Atapattu, Nathan Ross, Sithamparanathan Kandeepan, Chintha Tellambura
https://arxiv.org/abs/2506.12778

Dynamic Scheduling for Enhanced Performance in RIS-assisted Cooperative Network with Interference
Reconfigurable Intelligent Surfaces (RIS) have emerged as transformative technologies, enhancing spectral efficiency and improving interference management in multi-user cooperative communications. This paper investigates the integration of RIS with Flexible-Duplex (FlexD) communication, featuring dynamic scheduling capabilities, to mitigate unintended external interference in multi-user wireless networks. By leveraging the reconfigurability of RIS and dynamic scheduling, we propose a user-pair …

Wasserstein-Barycenter Consensus for Cooperative Multi-Agent Reinforcement Learning
Ali Baheri
https://arxiv.org/abs/2506.12497 https://

Wasserstein-Barycenter Consensus for Cooperative Multi-Agent Reinforcement Learning
Cooperative multi-agent reinforcement learning (MARL) demands principled mechanisms to align heterogeneous policies while preserving the capacity for specialized behavior. We introduce a novel consensus framework that defines the team strategy as the entropic-regularized $p$-Wasserstein barycenter of agents' joint state--action visitation measures. By augmenting each agent's policy objective with a soft penalty proportional to its Sinkhorn divergence from this barycenter, the proposed approach …

A Learning Framework For Cooperative Collision Avoidance of UAV Swarms Leveraging Domain Knowledge
Shuangyao Huang, Haibo Zhang, Zhiyi Huang
https://arxiv.org/abs/2507.10913

A Learning Framework For Cooperative Collision Avoidance of UAV Swarms Leveraging Domain Knowledge
This paper presents a multi-agent reinforcement learning (MARL) framework for cooperative collision avoidance of UAV swarms leveraging domain knowledge-driven reward. The reward is derived from knowledge in the domain of image processing, approximating contours on a two-dimensional field. By modeling obstacles as maxima on the field, collisions are inherently avoided as contours never go through peaks or intersect. Additionally, counters are smooth and energy-efficient. Our framework enables tr…

The Trump administration is thinking about adding 26 more countries
—most of them African
—to his travel ban list.
The Washington Post obtained a Trump administration memo that would give the 26 countries listed 60 days to capitulate to State Department demands.
Some countries were flagged for having “no competent or cooperative central government authority to produce reliable identity documents or other civil documents,”
or “government fraud.”
There was …

Trump Wants to Ban a Quarter of the World From Traveling to the U.S.
If put into effect, it could jeopardize future events like the 2026 World Cup and 2028 Olympics.

At the CTIF workshop in Brussels on copyright infrastructure, a cooperative project of the Finnish and the Estonian governments. I will talk about licensing linked data for trust in media

🔧 #Generators excel at lazy iteration and memory efficiency, implementing Iterator interface for foreach loops
⚡ #Fibers enable cooperative multitasking and nested suspension, perfect for #CLI

Screen Reader Users in the Vibe Coding Era: Adaptation, Empowerment, and New Accessibility Landscape
Nan Chen, Luna K. Qiu, Arran Zeyu Wang, Zilong Wang, Yuqing Yang
https://arxiv.org/abs/2506.13270

Screen Reader Users in the Vibe Coding Era: Adaptation, Empowerment, and New Accessibility Landscape
The rise of generative AI agents has reshaped human-computer interaction and computer-supported cooperative work by shifting users' roles from direct task execution to supervising machine-driven actions, especially in programming (e.g., "vibe coding"). However, there is limited understanding of how screen reader users engage with these systems in practice. To address this gap, we conducted a longitudinal study with 16 screen reader users, exploring their experiences with AI code assistants in d…

Trust-MARL: Trust-Based Multi-Agent Reinforcement Learning Framework for Cooperative On-Ramp Merging Control in Heterogeneous Traffic Flow
Jie Pan, Tianyi Wang, Christian Claudel, Jing Shi
https://arxiv.org/abs/2506.12600

Trust-MARL: Trust-Based Multi-Agent Reinforcement Learning Framework for Cooperative On-Ramp Merging Control in Heterogeneous Traffic Flow
Intelligent transportation systems require connected and automated vehicles (CAVs) to conduct safe and efficient cooperation with human-driven vehicles (HVs) in complex real-world traffic environments. However, the inherent unpredictability of human behaviour, especially at bottlenecks such as highway on-ramp merging areas, often disrupts traffic flow and compromises system performance. To address the challenge of cooperative on-ramp merging in heterogeneous traffic environments, this study pro…

Emergence of an Epsilon-Near-Zero Medium from Microscopic Atomic Principles
L. Ruks, J. Ruostekoski
https://arxiv.org/abs/2506.13294 https://

Emergence of an Epsilon-Near-Zero Medium from Microscopic Atomic Principles
We demonstrate that an effective near-zero refractive index can emerge from collective light scattering in a discrete atomic lattice, using essentially exact microscopic simulations. In a 25-layer array, cooperative response leads to over a thirtyfold increase in the effective optical wavelength within the medium, almost eliminating optical phase accumulation, with potential applications in spectroscopy and optical manipulation of quantum emitters. Crucially, the near-zero refractive index aris…

Cooperative Gradient Coding
Shudi Weng, Ming Xiao, Chao Ren, Mikael Skoglund
https://arxiv.org/abs/2507.05230 https://arxiv.org/pdf/2…

Cooperative Gradient Coding
This work studies gradient coding (GC) in the context of distributed training problems with unreliable communication. We propose cooperative GC (CoGC), a novel gradient-sharing-based GC framework that leverages cooperative communication among clients. This approach ultimately eliminates the need for dataset replication, making it both communication- and computation-efficient and suitable for federated learning (FL). By employing the standard GC decoding mechanism, CoGC yields strictly binary ou…

Unbounded sets of solutions of non-cooperative elliptic systems on symmetric spaces
Piotr Stefaniak
https://arxiv.org/abs/2506.08705 https://

Unbounded sets of solutions of non-cooperative elliptic systems on symmetric spaces
The aim of this paper is to show that, for a class of non-cooperative elliptic systems on compact symmetric spaces, any continuum of nontrivial solutions bifurcating from the set of trivial solutions is unbounded. The main tool is the degree for invariant strongly indefinite functionals. The analysis relies on the torus-equivariant structure of the Laplace--Beltrami eigenspaces. The result is obtained by ruling out return to the trivial branch in an equivariant version of the Rabinowitz alterna…

Cooperative Mapping, Localization, and Beam Management via Multi-Modal SLAM in ISAC Systems
Hang Que, Jie Yang, Tao Du, Shuqiang Xia, Chao-Kai Wen, Shi Jin
https://arxiv.org/abs/2507.05718

Cooperative Mapping, Localization, and Beam Management via Multi-Modal SLAM in ISAC Systems
Simultaneous localization and mapping (SLAM) plays a critical role in integrated sensing and communication (ISAC) systems for sixth-generation (6G) millimeter-wave (mmWave) networks, enabling environmental awareness and precise user equipment (UE) positioning. While cooperative multi-user SLAM has demonstrated potential in leveraging distributed sensing, its application within multi-modal ISAC systems remains limited, particularly in terms of theoretical modeling and communication-layer integra…

The algebraic structures of social organizations: the operad of cooperative games
Dylan Laplace Mermoud, Victor Roca i Lucio
https://arxiv.org/abs/2507.01969

The algebraic structures of social organizations: the operad of cooperative games
The main goal of this paper is to settle a conceptual framework for cooperative game theory in which the notion of composition/aggregation of games is the defining structure. This is done via the mathematical theory of algebraic operads: we start by endowing the collection of all cooperative games with any number of players with an operad structure, and we show that it generalises all the previous notions of sums, products and compositions of games considered by Owen, Shapley, von Neumann and M…

Generate Realistic Test Scenes for V2X Communication Systems
An Guo, Xinyu Gao, Chunrong Fang, Haoxiang Tian, Weisong Sun, Yanzhou Mu, Shuncheng Tang, Lei Ma, Zhenyu Chen
https://arxiv.org/abs/2506.07419

Generate Realistic Test Scenes for V2X Communication Systems
Accurately perceiving complex driving environments is essential for ensuring the safe operation of autonomous vehicles. With the tremendous progress in deep learning and communication technologies, cooperative perception with Vehicle-to-Everything (V2X) technologies has emerged as a solution to overcome the limitations of single-agent perception systems in perceiving distant objects and occlusions. Despite the considerable advancements, V2X cooperative perception systems require thorough testin…

Unconventional S-orbital state of Tb and cooperative Ru(4d)-Tb(4f) spin-ordering in strongly correlated 4d-4f system, Ba3TbRu2O9
E. Kushwaha, G. Roy, A. M. dos Santos, M. Kumar, S. Ghosh, T. Heitmann, T. Basu
https://arxiv.org/abs/2506.07717

Unconventional S-orbital state of Tb and cooperative Ru(4d)-Tb(4f) spin-ordering in strongly correlated 4d-4f system, Ba3TbRu2O9
The 6H-perovskite Ba3RRu2O9 (R = rare-earth), composed of Ru2O9 dimers connected through RO6 octahedra, exhibits an intriguing variety of magnetic ground states, ranging from non-magnetic to ferromagnetic and antiferromagnetic, depending on the specific R ion. In this study, we investigate the compound Ba3TbRu2O9 using magnetic susceptibility measurements and time-of-flight neutron diffraction experiments. Our combined bulk and microscopic analyses reveal that the Tb4+ (4f7) electronic configur…

Experimental observation of subabsorption
D. C. Gold, U. Saglam, S. Carpenter, A. Yadav, M. Beede, T. G. Walker, M. Saffman, D. D. Yavuz
https://arxiv.org/abs/2506.09872

Experimental observation of subabsorption
We predict and experimentally demonstrate a new type of collective (cooperative) coupling effect where a disordered atomic ensemble absorbs light with a rise-time longer (i. e., at a rate slower) than what is dictated by single-atom physics. This effect, which we name subabsorption, can be viewed as the absorptive analog of subradiance. The experiment is performed using a dilute ensemble of ultracold $^{87}$Rb atoms with a low optical depth, and time-resolving the absorption of a weak (tens of …

Semantic Communication for Cooperative Multi-Tasking over Rate-Limited Wireless Channels with Implicit Optimal Prior
Ahmad Halimi Razlighi, Carsten Bockelmann, Armin Dekorsy
https://arxiv.org/abs/2506.08944

Semantic Communication for Cooperative Multi-Tasking over Rate-Limited Wireless Channels with Implicit Optimal Prior
In this work, we expand the cooperative multi-task semantic communication framework (CMT-SemCom) introduced in [1], which divides the semantic encoder on the transmitter side into a common unit (CU) and multiple specific units (SUs), to a more applicable design. Our proposed system model addresses real-world constraints by introducing a general design that operates over rate-limited wireless channels. Further, we aim to tackle the rate-limit constraint, represented through the Kullback-Leibler …

On-board Mission Replanning for Adaptive Cooperative Multi-Robot Systems
Elim Kwan, Rehman Qureshi, Liam Fletcher, Colin Laganier, Victoria Nockles, Richard Walters
https://arxiv.org/abs/2506.06094

On-board Mission Replanning for Adaptive Cooperative Multi-Robot Systems
Cooperative autonomous robotic systems have significant potential for executing complex multi-task missions across space, air, ground, and maritime domains. But they commonly operate in remote, dynamic and hazardous environments, requiring rapid in-mission adaptation without reliance on fragile or slow communication links to centralised compute. Fast, on-board replanning algorithms are therefore needed to enhance resilience. Reinforcement Learning shows strong promise for efficiently solving mi…

A Cellular Automata Approach to Donation Game
Marcin Kowalik, Przemys{\l}aw Stok{\l}osa, Mateusz Grabowski, Janusz Starzyk, Pawe{\l} Raif
https://arxiv.org/abs/2507.11744

A Cellular Automata Approach to Donation Game
The donation game is a well-established framework for studying the emergence and evolution of cooperation in multi-agent systems. The cooperative behavior can be influenced by the environmental noise in partially observable settings and by the decision-making strategies of agents, which may incorporate not only reputation but also traits such as generosity and forgiveness. Traditional simulations often assume fully random interactions, where cooperation is tested between randomly selected agent…

Wireless Communication as an Information Sensor for Multi-agent Cooperative Perception: A Survey
Zhiying Song, Tenghui Xie, Fuxi Wen, Jun Li
https://arxiv.org/abs/2505.00747

Wireless Communication as an Information Sensor for Multi-agent Cooperative Perception: A Survey
Cooperative perception extends the perception capabilities of autonomous vehicles by enabling multi-agent information sharing via Vehicle-to-Everything (V2X) communication. Unlike traditional onboard sensors, V2X acts as a dynamic "information sensor" characterized by limited communication, heterogeneity, mobility, and scalability. This survey provides a comprehensive review of recent advancements from the perspective of information-centric cooperative perception, focusing on three key dimensio…

Solving Nash Equilibria in Nonlinear Differential Games for Common-Pool Resources
Yongyang Cai, Anastasios Xepapadeas, Aart de Zeeuw
https://arxiv.org/abs/2506.06646

Solving Nash Equilibria in Nonlinear Differential Games for Common-Pool Resources
Many resources are provided by an ecological system that is vulnerable to tipping when exceeding a certain level of pollution, with a sudden big loss of ecosystem services. An ecological system is usually also a common-pool resource and therefore vulnerable to suboptimal use resulting from non-cooperative behavior. An analysis requires methods to derive cooperative and non-cooperative solutions for managing a dynamical system with tipping points. Such a game is a differential game which has two…

Ok #Fediverse: if I was keen to bootstrap an Aotearoa-based tech services #cooperative, what coop models would people suggest I look at - looking for good descriptions of how they'd be set up, especially to recognise the contributions of those involved. All insights appreciated! I'…

Designing morphologies of soft medical devices using cooperative neuro coevolution
Hugo Alcaraz-Herrera, Michail-Antisthenis Tsompanas, Igor Balaz, Andrew Adamatzky
https://arxiv.org/abs/2506.03847

Designing morphologies of soft medical devices using cooperative neuro coevolution
Soft robots have proven to outperform traditional robots in applications related to propagation in geometrically constrained environments. Designing these robots and their controllers is an intricate task, since their building materials exhibit non-linear properties. Human designs may be biased; hence, alternative designing processes should be considered. We present a cooperative neuro coevolution approach to designing the morphologies of soft actuators and their controllers for applications in…

Joint attitude estimation and 3D neural reconstruction of non-cooperative space objects
Cl\'ement Forray, Pauline Delporte, Nicolas Delaygue, Florence Genin, Dawa Derksen
https://arxiv.org/abs/2506.20638

Joint attitude estimation and 3D neural reconstruction of non-cooperative space objects
Obtaining a better knowledge of the current state and behavior of objects orbiting Earth has proven to be essential for a range of applications such as active debris removal, in-orbit maintenance, or anomaly detection. 3D models represent a valuable source of information in the field of Space Situational Awareness (SSA). In this work, we leveraged Neural Radiance Fields (NeRF) to perform 3D reconstruction of non-cooperative space objects from simulated images. This scenario is challenging for N…

RADAR: a Radio-based Analytics for Dynamic Association and Recognition of pseudonyms in VANETs
Giovanni Gambigliani Zoccoli, Filip Valgimigli, Dario Stabili, Mirco Marchetti
https://arxiv.org/abs/2507.07732

RADAR: a Radio-based Analytics for Dynamic Association and Recognition of pseudonyms in VANETs
This paper presents RADAR, a tracking algorithm for vehicles participating in Cooperative Intelligent Transportation Systems (C-ITS) that exploits multiple radio signals emitted by a modern vehicle to break privacy-preserving pseudonym schemes deployed in VANETs. This study shows that by combining Dedicated Short Range Communication (DSRC) and Wi-Fi probe request messages broadcast by the vehicle, it is possible to improve tracking over standard de-anonymization approaches that only leverage DS…

Hardware Accelerated Neural Block Texture Compression with Cooperative Vectors
Belcour Laurent, Benyoub Anis
https://arxiv.org/abs/2506.06040 https://

Hardware Accelerated Neural Block Texture Compression with Cooperative Vectors
In this work, we present an extension to the neural texture compression method of Weinreich and colleagues [2024]. Like them, we leverage existing block compression methods which permit to use hardware texture filtering to store a neural representation of physically-based rendering (PBR) texture sets (including albedo, normal maps, roughness, etc.). However, we show that low dynamic range block compression formats still make the solution viable. Thanks to this, we show that we can achieve highe…

Secure Cooperative Gradient Coding: Optimality, Reliability, and Global Privacy
Shudi Weng
https://arxiv.org/abs/2507.07565 https://a…

Secure Cooperative Gradient Coding: Optimality, Reliability, and Global Privacy
This paper studies privacy-sensitive federated learning (FL) with unreliable communication, focusing on secure aggregation and straggler mitigation. While secure aggregation cryptographically reconstructs the global model without exposing client updates, random link failures disrupt its key coordination, degrading model accuracy. Moreover, unreliable communication can lead to objective inconsistency, causing the global model to converge to arbitrary, sub-optimal points far from the intended opt…

Replaced article(s) found for cs.MA. https://arxiv.org/list/cs.MA/new
[1/1]:
Robust Cooperative Multi-Agent Reinforcement Learning:A Mean-Field Type Game Perspective

Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models
Marouane Il Idrissi, Agathe Fernandes Machado, Arthur Charpentier
https://arxiv.org/abs/2506.13900

Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models
Cooperative game theory has become a cornerstone of post-hoc interpretability in machine learning, largely through the use of Shapley values. Yet, despite their widespread adoption, Shapley-based methods often rest on axiomatic justifications whose relevance to feature attribution remains debatable. In this paper, we revisit cooperative game theory from an interpretability perspective and argue for a broader and more principled use of its tools. We highlight two general families of efficient al…

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[4/6]:
- A Cascading Cooperative Multi-agent Framework for On-ramp Merging Control Integrating Large Langu...
Miao Zhang, Zhenlong Fang, Tianyi Wang, Qian Zhang, Shuai Lu, Junfeng Jiao, Tianyu Shi

Q-learning-based Hierarchical Cooperative Local Search for Steelmaking-continuous Casting Scheduling Problem
Yang Lv, Rong Hu, Bin Qian, Jian-Bo Yang
https://arxiv.org/abs/2506.08608

Q-learning-based Hierarchical Cooperative Local Search for Steelmaking-continuous Casting Scheduling Problem
The steelmaking continuous casting scheduling problem (SCCSP) is a critical and complex challenge in modern steel production, requiring the coordinated assignment and sequencing of steel charges across multiple production stages. Efficient scheduling not only enhances productivity but also significantly reduces energy consumption. However, both traditional heuristics (e.g., two-stage local search) and recent metaheuristics often struggle to adapt to the dynamic characteristics of practical SCCS…

Cooperation and the Design of Public Goods
J. Carlos Mart\'inez Mori, Alejandro Toriello
https://arxiv.org/abs/2506.05251 https://

Cooperation and the Design of Public Goods
We consider the cooperative elements that arise in the design of public goods, such as transportation policies and infrastructure. These involve a variety of stakeholders: governments, businesses, advocates, and users. Their eventual deployment depends on the decision maker's ability to garner sufficient support from each of these groups; we formalize these strategic requirements from the perspective of cooperative game theory. Specifically, we introduce non-transferable utility, linear product…

UAV-UGV Cooperative Trajectory Optimization and Task Allocation for Medical Rescue Tasks in Post-Disaster Environments
Kaiyuan Chen, Wanpeng Zhao, Yongxi Liu, Yuanqing Xia, Wannian Liang, Shuo Wang
https://arxiv.org/abs/2506.06136

UAV-UGV Cooperative Trajectory Optimization and Task Allocation for Medical Rescue Tasks in Post-Disaster Environments
In post-disaster scenarios, rapid and efficient delivery of medical resources is critical and challenging due to severe damage to infrastructure. To provide an optimized solution, we propose a cooperative trajectory optimization and task allocation framework leveraging unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). This study integrates a Genetic Algorithm (GA) for efficient task allocation among multiple UAVs and UGVs, and employs an informed-RRT* (Rapidly-exploring Rando…

Trump regime plans to cancel all climate research at @noaa.gov , including its Mauna Loa CO2 measurements, running since 1958.
Last year's budget was $220 million. Next year's would be $0.
https://bsky.app/profile/rarohde.bsky.social/post/3lsucn5ckys2k

Robert Rohde (@rarohde.bsky.social)
Proposed NOAA budget zeros out ALL climate laboratories and cooperative institutions. GFDL, NSSL, GML, etc. This appears to also end the US greenhouse gas sampling network, including at Mauna Loa, the oldest continuous carbon dioxide monitoring site on Earth. https://www.commerce.gov/sites/default/files/2025-06/NOAA-FY2026-Congressional-Budget-Submission.pdf

Graph Learning for Cooperative Cell-Free ISAC Systems: From Optimization to Estimation
Peng Jiang, Ming Li, Rang Liu, Qian Liu
https://arxiv.org/abs/2507.06612

Graph Learning for Cooperative Cell-Free ISAC Systems: From Optimization to Estimation
Cell-free integrated sensing and communication (ISAC) systems have emerged as a promising paradigm for sixth-generation (6G) networks, enabling simultaneous high-rate data transmission and high-precision radar sensing through cooperative distributed access points (APs). Fully exploiting these capabilities requires a unified design that bridges system-level optimization with multi-target parameter estimation. This paper proposes an end-to-end graph learning approach to close this gap, modeling t…

Drift-Adaptive Slicing-Based Resource Management for Cooperative ISAC Networks
Shisheng Hu, Jie Gao, Xue Qin, Conghao Zhou, Xinyu Huang, Mushu Li, Mingcheng He, Xuemin Shen
https://arxiv.org/abs/2506.20762

Drift-Adaptive Slicing-Based Resource Management for Cooperative ISAC Networks
In this paper, we propose a novel drift-adaptive slicing-based resource management scheme for cooperative integrated sensing and communication (ISAC) networks. Particularly, we establish two network slices to provide sensing and communication services, respectively. In the large-timescale planning for the slices, we partition the sensing region of interest (RoI) of each mobile device and reserve network resources accordingly, facilitating low-complexity distance-based sensing target assignment …

"This tree may reach the age of 250 years and is fast growing the first third of those years, then grows slowly."
I love how trees make us think long term. If I plant one of these tomorrow, I'll be long gone by the time that slowing of growth happens (250 / 3 = 83 years).
https://www.

Fermionic operatorial model of a system with competitive and cooperative interactions
M. Gorgone, G. Inferrera, F. Oliveri
https://arxiv.org/abs/2505.21554

Fermionic operatorial model of a system with competitive and cooperative interactions
An operatorial model of a system made by $N$ agents interacting each other with mechanisms that can be thought of as cooperative or competitive is presented. We associate to each agent an annihilation, creation and number fermionic operator, and interpret the mean values of the number operators over an initial condition as measures of the agents' wealth status. The dynamics of the system is assumed to be ruled by a Hermitian Hamiltonian operator $\mathcal{H}$, and the classical Heisenberg view …

"French company offers router capable of redirecting surplus solar to water heating"
#France #SolarPower #Energy #Renewables

French company offers router capable of redirecting surplus solar to water heating
French energy cooperative Solarcoop has launched a solar router that redirects surplus photovoltaic power from self-consumption systems to electric water heaters or other resistive loads, and can also control additional devices such as heat pumps.

Topology of the Generalized Nash Equilibrium Problem
Matija Blagojevi\'c, Christof Sch\"utte
https://arxiv.org/abs/2507.03753 https://

Topology of the Generalized Nash Equilibrium Problem
The Generalized Nash Equilibrium Problem refers to the question of the existence of a Nash equilibrium in an abstract economy. This model is due to Kenneth J. Arrow and Gerard Debreu in their pioneering work from 1954. An abstract economy is an extension of John Nash's original concept of a non-cooperative game from the 1950's. Here players selfishly seek to maximize their profits, which may depend on the others' choices. The novelty of an abstract economy is that the players may now mutually c…

Learned Off-Grid Imager for Low-Altitude Economy with Cooperative ISAC Network
Yixuan Huang, Jie Yang, Shuqiang Xia, Chao-Kai Wen, Shi Jin
https://arxiv.org/abs/2506.07799

Learned Off-Grid Imager for Low-Altitude Economy with Cooperative ISAC Network
The low-altitude economy is emerging as a key driver of future economic growth, necessitating effective flight activity surveillance using existing mobile cellular network sensing capabilities. However, traditional monostatic and localizationbased sensing methods face challenges in fusing sensing results and matching channel parameters. To address these challenges, we model low-altitude surveillance as a compressed sensing (CS)-based imaging problem by leveraging the cooperation of multiple bas…

Matroid isomorphism games
Daniel Corey, Simon Schmidt, Marcel Wack
https://arxiv.org/abs/2507.06225 https://arxiv.org/pdf/2507.06225

Matroid isomorphism games
We define and study a collection of matroid isomorphism games corresponding to various axiomatic characterizations of matroids. These are nonlocal games played between two cooperative players. Each game is played on two matroids, and the matroids are isomorphic if and only if the game has a perfect classical winning strategy. We define notions of quantum isomorphism in terms of perfect quantum commuting strategies, and we find a pair of nonisomorphic matroids that are quantum isomorphic. We als…

Neutral theory of cooperators
Jordi Pi\~nero, Artemy Kolchinsky, Sidney Redner, Ricard Sol\'e
https://arxiv.org/abs/2506.09737 https://

Neutral theory of cooperators
Mutualistic interactions are widespread in nature, from plant communities and microbiomes to human organizations. Along with competition for resources, cooperative interactions shape biodiversity and contribute to the robustness of complex ecosystems. We present a stochastic neutral theory of cooperator species. Our model shares with the classic neutral theory of biodiversity the assumption that all species are equivalent, but crucially differs in requiring cooperation between species for repli…

PAL: Designing Conversational Agents as Scalable, Cooperative Patient Simulators for Palliative-Care Training
Neil K. R. Sehgal, Hita Kambhamettu, Allen Chang, Andrew Zhu, Lyle Ungar, Sharath Chandra Guntuku
https://arxiv.org/abs/2507.02122

PAL: Designing Conversational Agents as Scalable, Cooperative Patient Simulators for Palliative-Care Training
Effective communication in serious illness and palliative care is essential but often under-taught due to limited access to training resources like standardized patients. We present PAL (Palliative Assisted Learning-bot), a conversational system that simulates emotionally nuanced patient interactions and delivers structured feedback grounded in an existing empathy-based framework. PAL supports text and voice modalities and is designed to scaffold clinical skill-building through repeated, low-co…

A distributed motion planning approach to cooperative underwater acoustic source tracking and pursuit
Andrea Tiranti, Francesco Wanderlingh, Enrico Simetti, Marco Baglietto, Giovanni Indiveri, Antonio Pascoal
https://arxiv.org/abs/2506.07877

A distributed motion planning approach to cooperative underwater acoustic source tracking and pursuit
This paper addresses the problem of underwater acoustic source tracking and pursuit with a team of autonomous underwater vehicles. Producing distributed control strategies in an underwater sensor network is not trivial since communication is primarily acoustic, which makes it intermittent and often plagued with major difficulties. For this reason, we propose an optimization scheme based on a Partially Observable Markov Decision Process for improving the performance of underwater mobile sensor n…

Today I brought by bike to the yearly service to Cooperative, rode back with a rental and got a bunch of new vinyl at Rave Up.

Confidence Boosts Trust-Based Resilience in Cooperative Multi-Robot Systems
Luca Ballotta, \'Aron V\'ek\'assy, Stephanie Gil, Michal Yemini
https://arxiv.org/abs/2506.08807

Confidence Boosts Trust-Based Resilience in Cooperative Multi-Robot Systems
Wireless communication-based multi-robot systems open the door to cyberattacks that can disrupt safety and performance of collaborative robots. The physical channel supporting inter-robot communication offers an attractive opportunity to decouple the detection of malicious robots from task-relevant data exchange between legitimate robots. Yet, trustworthiness indications coming from physical channels are uncertain and must be handled with this in mind. In this paper, we propose a resilient prot…

Exploring a Specialized Eccentricity-Based Deep Neural Network Model to Simulate Visual Attention
Manvi Jain
https://arxiv.org/abs/2507.05031 https://

Exploring a Specialized Eccentricity-Based Deep Neural Network Model to Simulate Visual Attention
While visual attention theories abound, neurodevelopmental research remains constrained by infants' unreliable responses and limited attention spans. Through collaboration with Project Prakash, we accessed a unique population: patients gaining vision later in life. This cohort enables investigation of visual process development in cognitively mature, cooperative participants rather than infants. We collected data from pre-operation patients, post-operation patients tracked longitudinally (1, 3,…

CoInfra: A Large-Scale Cooperative Infrastructure Perception System and Dataset in Adverse Weather
Minghao Ning, Yufeng Yang, Keqi Shu, Shucheng Huang, Jiaming Zhong, Maryam Salehi, Mahdi Rahmani, Yukun Lu, Chen Sun, Aladdin Saleh, Ehsan Hashemi, Amir Khajepour
https://arxiv.org/abs/2507.02245

CoInfra: A Large-Scale Cooperative Infrastructure Perception System and Dataset in Adverse Weather
We present CoInfra, a large-scale cooperative infrastructure perception system and dataset designed to advance robust multi-agent perception under real-world and adverse weather conditions. The CoInfra system includes 14 fully synchronized sensor nodes, each equipped with dual RGB cameras and a LiDAR, deployed across a shared region and operating continuously to capture all traffic participants in real-time. A robust, delay-aware synchronization protocol and a scalable system architecture that …

Planar pulsating traveling wave solutions of non-cooperative Fisher--KPP systems in space-time periodic media
L\'eo Girardin (CNRS, ICJ, MMCS), Gr\'egoire Nadin (IDP, CNRS)
https://arxiv.org/abs/2506.22003

Planar pulsating traveling wave solutions of non-cooperative Fisher--KPP systems in space-time periodic media
Non-cooperative Fisher-KPP systems with space-time periodic coefficients are motivated for instance by models for structured populations evolving in periodic environments. This paper is concerned with entire solutions describing the invasion of open space by a persistent population at constant speed. These solutions are important in the understanding of long-time behaviors for the Cauchy problem. Adapting methods developed for scalar equations satisfying the comparison principle as well as meth…

Replaced article(s) found for physics.pop-ph. https://arxiv.org/list/physics.pop-ph/new/
[1/1]:
Cooperative Behavior in Pre-State Societies: An Agent-Based Approach of the Aksum Civilization

Chirality Amplification and Deracemization in Liquid Crystals
Matthew J. Deutsch, Robin L. B. Selinger, Paul van der Schoot
https://arxiv.org/abs/2506.05053

Chirality Amplification and Deracemization in Liquid Crystals
Liquid crystal mesophases of achiral molecules are normally achiral, yet in a few materials they spontaneously deracemize and form right- and left-handed chiral domains. One mechanism that drives deracemization is molecular shape fluctuations between axial chiral conformations, where molecular interactions favor matching chirality and promote helical twist. Cooperative chiral ordering may also play a role in chirality amplification, as when a tiny fraction of chiral dopant drives a nematic phas…

Graph-Based Complexity Metrics for Multi-Agent Curriculum Learning: A Validated Approach to Task Ordering in Cooperative Coordination Environments
Farhaan Ebadulla, Dharini Hindlatti, Srinivaasan NS, Apoorva VH, Ayman Aftab
https://arxiv.org/abs/2507.07074

Graph-Based Complexity Metrics for Multi-Agent Curriculum Learning: A Validated Approach to Task Ordering in Cooperative Coordination Environments
Multi-agent reinforcement learning (MARL) faces significant challenges in task sequencing and curriculum design, particularly for cooperative coordination scenarios. While curriculum learning has demonstrated success in single-agent domains, principled approaches for multi-agent coordination remain limited due to the absence of validated task complexity metrics. This approach presents a graph-based coordination complexity metric that integrates agent dependency entropy, spatial interference pat…

Two-stage Stochastic Assignment Games
Laura Sanit\`a, Lucy Verberk
https://arxiv.org/abs/2506.01509 https://arxiv.org/pdf/2506.01509

Two-stage Stochastic Assignment Games
In this paper, we study a two-stage stochastic version of the assignment game, which is a fundamental cooperative game. Given an initial setting, the set of players may change in the second stage according to some probability distribution, and the goal is to find core solutions that are minimally modified. When the probability distribution is given explicitly, we observe that the problem is polynomial time solvable, as it can be modeled as an LP. More interestingly, we prove that the underlyi…

Two-Person Cooperative Games with delta-Rationality
Fang-Fang Tang, Yongsheng Xu
https://arxiv.org/abs/2506.16465 https://arxiv.org/p…

Two-Person Cooperative Games with delta-Rationality
A player's payoff is modeled as consisting of two parts: a rational-value part and a distortion-value part. It is argued that the (total) payoff function should be used to explain and predict the behaviors of the players, while the rational value function should be used to conduct welfare analysis of the final outcome. We use the Nash demand game to illustrate our model.

Minimal balanced collections and their applications to core stability and other topics of game theory
Dylan Laplace Mermoud, Michel Grabisch, Peter Sudh\"olter
https://arxiv.org/abs/2507.05898

Minimal balanced collections and their applications to core stability and other topics of game theory
Minimal balanced collections are a generalization of partitions of a finite set of n elements and have important applications in cooperative game theory and discrete mathematics. However, their number is not known beyond n = 4. In this paper we investigate the problem of generating minimal balanced collections and implement the Peleg algorithm, permitting to generate all minimal balanced collections till n = 7. Secondly, we provide practical algorithms to check many properties of coalitions and…

V2X Intention Sharing for Cooperative Electrically Power-Assisted Cycles
Felipe Valle Quiroz, Johan Elfing, Joel P{\aa}lsson, Elena Haller, Oscar Amador Molina
https://arxiv.org/abs/2506.22223

V2X Intention Sharing for Cooperative Electrically Power-Assisted Cycles
This paper introduces a novel intention-sharing mechanism for Electrically Power-Assisted Cycles (EPACs) within V2X communication frameworks, enhancing the ETSI VRU Awareness Message (VAM) protocol. The method replaces discrete predicted trajectory points with a compact elliptical geographical area representation derived via quadratic polynomial fitting and Least Squares Method (LSM). This approach encodes trajectory predictions with fixed-size data payloads, independent of the number of foreca…

Cooperative Target Capture in 3D Engagements over Switched Dynamic Graphs
Abhinav Sinha, Shashi Ranjan Kumar
https://arxiv.org/abs/2507.01350 https://

Cooperative Target Capture in 3D Engagements over Switched Dynamic Graphs
This paper presents a leaderless cooperative guidance strategy for simultaneous time-constrained interception of a stationary target when the interceptors exchange information over switched dynamic graphs. We specifically focus on scenarios when the interceptors lack radial acceleration capabilities, relying solely on their lateral acceleration components. This consideration aligns with their inherent kinematic turn constraints. The proposed strategy explicitly addresses the complexities of cou…

When Is Diversity Rewarded in Cooperative Multi-Agent Learning?
Michael Amir, Matteo Bettini, Amanda Prorok
https://arxiv.org/abs/2506.09434 https://

When Is Diversity Rewarded in Cooperative Multi-Agent Learning?
The success of teams in robotics, nature, and society often depends on the division of labor among diverse specialists; however, a principled explanation for when such diversity surpasses a homogeneous team is still missing. Focusing on multi-agent task allocation problems, our goal is to study this question from the perspective of reward design: what kinds of objectives are best suited for heterogeneous teams? We first consider an instantaneous, non-spatial setting where the global reward is b…

Digital Twin-Empowered Cooperative Autonomous Car-sharing Services: Proof-of-Concept
Kazuma Nonomura, Kui Wang, Zongdian Li, Tao Yu, Kei Sakaguchi
https://arxiv.org/abs/2504.20542

Cooperative Sensing in Cell-free Massive MIMO ISAC Systems: Performance Optimization and Signal Processing
Haotian Liu, Zhiqing Wei, Luyang Sun, Ruizhong Xu, Yixin Zhang, Zhiyong Feng
https://arxiv.org/abs/2506.23473

Cooperative Sensing in Cell-free Massive MIMO ISAC Systems: Performance Optimization and Signal Processing
Integrated sensing and communication (ISAC), as a technology enabled seamless connection between communication and sensing, is regarded a core enabling technology for these applications. However, the accuracy of single-node sensing in ISAC system is limited, prompting the emergence of multi-node cooperative sensing. In multi-node cooperative sensing, the synchronization error limits the sensing accuracy, which can be mitigated by the architecture of cell-free massive multi-input multi-output (C…

V2X-REALM: Vision-Language Model-Based Robust End-to-End Cooperative Autonomous Driving with Adaptive Long-Tail Modeling
Junwei You, Pei Li, Zhuoyu Jiang, Zilin Huang, Rui Gan, Haotian Shi, Bin Ran
https://arxiv.org/abs/2506.21041

V2X-REALM: Vision-Language Model-Based Robust End-to-End Cooperative Autonomous Driving with Adaptive Long-Tail Modeling
Ensuring robust planning and decision-making under rare, diverse, and visually degraded long-tail scenarios remains a fundamental challenge for autonomous driving in urban environments. This issue becomes more critical in cooperative settings, where vehicles and infrastructure jointly perceive and reason across complex environments. To address this challenge, we propose V2X-REALM, a vision-language model (VLM)-based framework with adaptive multimodal learning for robust cooperative autonomous d…

RIS-Aided Cooperative ISAC Networks for Structural Health Monitoring
Jie Yang, Chao-Kai Wen, Xiao Li, Shi Jin
https://arxiv.org/abs/2507.02731 https://

RIS-Aided Cooperative ISAC Networks for Structural Health Monitoring
Integrated sensing and communication (ISAC) is a key feature of future cellular systems, enabling applications such as intruder detection, monitoring, and tracking using the same infrastructure. However, its potential for structural health monitoring (SHM), which requires the detection of slow and subtle structural changes, remains largely unexplored due to challenges such as multipath interference and the need for ultra-high sensing precision. This study introduces a novel theoretical framewor…

Infrastructuring Contestability: A Framework for Community-Defined AI Value Pluralism
Andreas Mayer
https://arxiv.org/abs/2507.05187 https://

Infrastructuring Contestability: A Framework for Community-Defined AI Value Pluralism
The proliferation of AI-driven systems presents a fundamental challenge to Human-Computer Interaction (HCI) and Computer-Supported Cooperative Work (CSCW), often diminishing user agency and failing to account for value pluralism. Current approaches to value alignment, which rely on centralized, top-down definitions, lack the mechanisms for meaningful contestability. This leaves users and communities unable to challenge or shape the values embedded in the systems that govern their digital lives,…

An Improved Grey Wolf Optimizer Inspired by Advanced Cooperative Predation for UAV Shortest Path Planning
Zuhao Teng, Qian Dong, Ze Zhang, Shuangyao Huang, Wenzhang Zhang, Jingchen Wang, Ji Li, Xi Chen
https://arxiv.org/abs/2506.03663

An Improved Grey Wolf Optimizer Inspired by Advanced Cooperative Predation for UAV Shortest Path Planning
With the widespread application of Unmanned Aerial Vehicles (UAVs) in domains like military reconnaissance, emergency rescue, and logistics delivery, efficiently planning the shortest flight path has become a critical challenge. Traditional heuristic-based methods often suffer from the inability to escape from local optima, which limits their effectiveness in finding the shortest path. To address these issues, a novel Improved Grey Wolf Optimizer (IGWO) is presented in this study. The proposed …

STCLocker: Deadlock Avoidance Testing for Autonomous Driving Systems
Mingfei Cheng, Renzhi Wang, Xiaofei Xie, Yuan Zhou, Lei Ma
https://arxiv.org/abs/2506.23995

STCLocker: Deadlock Avoidance Testing for Autonomous Driving Systems
Autonomous Driving System (ADS) testing is essential to ensure the safety and reliability of autonomous vehicles (AVs) before deployment. However, existing techniques primarily focus on evaluating ADS functionalities in single-AV settings. As ADSs are increasingly deployed in multi-AV traffic, it becomes crucial to assess their cooperative performance, particularly regarding deadlocks, a fundamental coordination failure in which multiple AVs enter a circular waiting state indefinitely, resultin…

Direct reciprocity in asynchronous interactions
Ketian Sun, Qi Su, Long Wang
https://arxiv.org/abs/2506.04264 https://arxiv.org/pdf/2…

Direct reciprocity in asynchronous interactions
Cooperation is vital for the survival of living systems but is challenging due to the costs borne by altruistic individuals. Direct reciprocity, where actions are based on past encounters, is a key mechanism fostering cooperation. However, most studies assume synchronous decision-making, whereas real-world interactions are often asynchronous, with individuals acting in sequence. This asynchrony can undermine standard cooperative strategies like Tit-for-Tat and Win-Stay Lose-Shift. To better und…

A Survey on the Role of Artificial Intelligence and Machine Learning in 6G-V2X Applications
Donglin Wang, Anjie Qiu, Qiuheng Zhou, Hans D. Schotten
https://arxiv.org/abs/2506.09512

A Survey on the Role of Artificial Intelligence and Machine Learning in 6G-V2X Applications
The rapid advancement of Vehicle-to-Everything (V2X) communication is transforming Intelligent Transportation Systems (ITS), with 6G networks expected to provide ultra-reliable, low-latency, and high-capacity connectivity for Connected and Autonomous Vehicles (CAVs). Artificial Intelligence (AI) and Machine Learning (ML) have emerged as key enablers in optimizing V2X communication by enhancing network management, predictive analytics, security, and cooperative driving due to their outstanding p…

A Survey of Multi Agent Reinforcement Learning: Federated Learning and Cooperative and Noncooperative Decentralized Regimes
Kemboi Cheruiyot, Nickson Kiprotich, Vyacheslav Kungurtsev, Kennedy Mugo, Vivian Mwirigi, Marvin Ngesa
https://arxiv.org/abs/2507.06278

A Survey of Multi Agent Reinforcement Learning: Federated Learning and Cooperative and Noncooperative Decentralized Regimes
The increasing interest in research and innovation towards the development of autonomous agents presents a number of complex yet important scenarios of multiple AI Agents interacting with each other in an environment. The particular setting can be understood as exhibiting three possibly topologies of interaction - centrally coordinated cooperation, ad-hoc interaction and cooperation, and settings with noncooperative incentive structures. This article presents a comprehensive survey of all three…

Dynamic Avalanches: Rate-Controlled Switching and Race Conditions
Lishuai Jin, Martin van Hecke
https://arxiv.org/abs/2507.02387 https://

Dynamic Avalanches: Rate-Controlled Switching and Race Conditions
Avalanches are rapid cascades of rearrangements driven by cooperative flipping of hysteretic local elements. Here we show that flipping dynamics and race conditions -- where multiple elements become unstable simultaneously -- give rise to dynamic avalanches that cannot be captured by static models of interacting elements. We realize dynamic avalanches in metamaterials with controlled flipping times, and demonstrate how this allows to modify, promote, and direct avalanche behavior. Our work eluc…

Dynamic real-time multi-UAV cooperative mission planning method under multiple constraints
Chenglou Liu, Yufeng Lu, Fangfang Xie, Tingwei Ji, Yao Zheng
https://arxiv.org/abs/2506.02365

Dynamic real-time multi-UAV cooperative mission planning method under multiple constraints
As UAV popularity soars, so does the mission planning associated with it. The classical approaches suffer from the triple problems of decoupled of task assignment and path planning, poor real-time performance and limited adaptability. Aiming at these challenges, this paper proposes a dynamic real-time multi-UAV collaborative mission planning algorithm based on Dubins paths under a distributed formation structure. Dubins path with multiple advantages bridges the gap between task assignment and p…

Crowdsourcing Ubiquitous Indoor Localization with Non-Cooperative Wi-Fi Ranging
Emerson Sie, Enguang Fan, Federico Cifuentes-Urtubey, Deepak Vasisht
https://arxiv.org/abs/2506.18317

Crowdsourcing Ubiquitous Indoor Localization with Non-Cooperative Wi-Fi Ranging
Indoor localization opens the path to potentially transformative applications. Although many indoor localization methods have been proposed over the years, they remain too impractical for widespread deployment in the real world. In this paper, we introduce PeepLoc, a deployable and scalable Wi-Fi-based solution for indoor localization that relies only on pre-existing devices and infrastructure. Specifically, PeepLoc works on any mobile device with an unmodified Wi-Fi transceiver and in any indo…

Cooperative Circumnavigation for Multi-Quadrotor Systems via Onboard Sensing
Xueming Liu, Lin Li, Xiang Zhou, Qingrui Zhang, Tianjiang Hu
https://arxiv.org/abs/2506.20954

Cooperative Circumnavigation for Multi-Quadrotor Systems via Onboard Sensing
A cooperative circumnavigation framework is proposed for multi-quadrotor systems to enclose and track a moving target without reliance on external localization systems. The distinct relationships between quadrotor-quadrotor and quadrotor-target interactions are evaluated using a heterogeneous perception strategy and corresponding state estimation algorithms. A modified Kalman filter is developed to fuse visual-inertial odometry with range measurements to enhance the accuracy of inter-quadrotor …

Signal Prediction for Loss Mitigation in Tactile Internet: A Leader-Follower Game-Theoretic Approach
Mohammad Ali Vahedifar, Qi Zhang
https://arxiv.org/abs/2507.07692

Signal Prediction for Loss Mitigation in Tactile Internet: A Leader-Follower Game-Theoretic Approach
Tactile Internet (TI) requires achieving ultra-low latency and highly reliable packet delivery for haptic signals. In the presence of packet loss and delay, the signal prediction method provides a viable solution for recovering the missing signals. To this end, we introduce the Leader-Follower (LeFo) approach based on a cooperative Stackelberg game, which enables both users and robots to learn and predict actions. With accurate prediction, the teleoperation system can safely relax its strict de…

Cooperative Sensing and Communication Beamforming Design for Low-Altitude Economy
Fangzhi Li, Zhichu Ren, Cunhua Pan, Hong Ren, Jing Jin, Qixing Wang, Jiangzhou Wang
https://arxiv.org/abs/2506.20244

Cooperative Sensing and Communication Beamforming Design for Low-Altitude Economy
To empower the low-altitude economy with high-accuracy sensing and high-rate communication, this paper proposes a cooperative integrated sensing and communication (ISAC) framework for aerial-ground networks. In the proposed system, the ground base stations (BSs) cooperatively serve the unmanned aerial vehicles (UAVs), which are equipped for either joint communication and sensing or sensing-only operations. The BSs employ coordinated beamforming to simultaneously transmit communication and sensi…

LAMARL: LLM-Aided Multi-Agent Reinforcement Learning for Cooperative Policy Generation
Guobin Zhu, Rui Zhou, Wenkang Ji, Shiyu Zhao
https://arxiv.org/abs/2506.01538

LAMARL: LLM-Aided Multi-Agent Reinforcement Learning for Cooperative Policy Generation
Although Multi-Agent Reinforcement Learning (MARL) is effective for complex multi-robot tasks, it suffers from low sample efficiency and requires iterative manual reward tuning. Large Language Models (LLMs) have shown promise in single-robot settings, but their application in multi-robot systems remains largely unexplored. This paper introduces a novel LLM-Aided MARL (LAMARL) approach, which integrates MARL with LLMs, significantly enhancing sample efficiency without requiring manual design. LA…

Two-Sided Manipulation Games in Stable Matching Markets
Hadi Hosseini, Grzegorz Lisowski, Shraddha Pathak
https://arxiv.org/abs/2506.00554 https://

Two-Sided Manipulation Games in Stable Matching Markets
The Deferred Acceptance (DA) algorithm is an elegant procedure for finding a stable matching in two-sided matching markets. It ensures that no pair of agents prefers each other to their matched partners. In this work, we initiate the study of two-sided manipulations in matching markets as non-cooperative games. We introduce the accomplice manipulation game, where a man misreports to help a specific woman obtain a better partner, whenever possible. We provide a polynomial time algorithm for find…

Cooperative Bistatic ISAC Systems for Low-Altitude Economy
Zhenkun Zhang, Yining Xu, Cunhua Pan, Hong Ren, Yiming Yu, Jiangzhou Wang
https://arxiv.org/abs/2506.18067

Cooperative Bistatic ISAC Systems for Low-Altitude Economy
The burgeoning low-altitude economy (LAE) necessitates integrated sensing and communication (ISAC) systems capable of high-accuracy multi-target localization and velocity estimation under hardware and coverage constraints inherent in conventional ISAC architectures. This paper addresses these challenges by proposing a cooperative bistatic ISAC framework within MIMO-OFDM cellular networks, enabling robust sensing services for LAE applications through standardized 5G New Radio (NR) infrastructure…

VoI-aware Scheduling Schemes for Multi-Agent Formation Control
Federico Chiariotti, Marco Fabris
https://arxiv.org/abs/2507.06392 https://

VoI-aware Scheduling Schemes for Multi-Agent Formation Control
Formation control allows agents to maintain geometric patterns using local information, but most existing methods assume ideal communication. This paper introduces a goal-oriented framework combining control, cooperative positioning, and communication scheduling for first-order formation tracking. Each agent estimates its position using 6G network-based triangulation, and the scheduling of information updates is governed by Age of Information (AoI) and Value of Information (VoI) metrics. We des…

To Embody or Not: The Effect Of Embodiment On User Perception Of LLM-based Conversational Agents
Kyra Wang, Boon-Kiat Quek, Jessica Goh, Dorien Herremans
https://arxiv.org/abs/2506.02514

To Embody or Not: The Effect Of Embodiment On User Perception Of LLM-based Conversational Agents
Embodiment in conversational agents (CAs) refers to the physical or visual representation of these agents, which can significantly influence user perception and interaction. Limited work has been done examining the effect of embodiment on the perception of CAs utilizing modern large language models (LLMs) in non-hierarchical cooperative tasks, a common use case of CAs as more powerful models become widely available for general use. To bridge this research gap, we conducted a mixed-methods withi…

Joint Target Acquisition and Refined Position Estimation in OFDM-based ISAC Networks
Lorenzo Pucci, Andrea Giorgetti
https://arxiv.org/abs/2507.07081 https…

Joint Target Acquisition and Refined Position Estimation in OFDM-based ISAC Networks
This paper addresses joint target acquisition and position estimation in an OFDM-based integrated sensing and communication (ISAC) network with base station (BS) cooperation via a fusion center. A two-stage framework is proposed: in the first stage, each BS computes range-angle maps to detect targets and estimate coarse positions, exploiting spatial diversity. In the second stage, refined localization is performed using a cooperative maximum likelihood (ML) estimator over predefined regions of …

A Cooperative Contactless Object Transport with Acoustic Robots
Narsimlu Kemsaram, Akin Delibasi, James Hardwick, Bonot Gautam, Diego Martinez Plasencia, Sriram Subramanian
https://arxiv.org/abs/2506.13957

A Cooperative Contactless Object Transport with Acoustic Robots
Cooperative transport, the simultaneous movement of an object by multiple agents, has been widely observed in biological systems such as ant colonies, which improve efficiency and adaptability in dynamic environments. Inspired by these natural phenomena, we present a novel acoustic robotic system for the transport of contactless objects in mid-air. Our system leverages phased ultrasonic transducers and a robotic control system onboard to generate localized acoustic pressure fields, enabling pre…

Dual-UAV-Aided Covert Communications for Air-to-Ground ISAC Networks
Jingke Sun, Liang Yang, Alexandros-Apostolos A. Boulogeorgos, Theodoros A. Tsiftsis, Hongwu Liu
https://arxiv.org/abs/2506.00601

Dual-UAV-Aided Covert Communications for Air-to-Ground ISAC Networks
To enhance both the sensing and covert communication performance, a dual-unmanned aerial vehicle (UAV)-aided scheme is proposed for integrated sensing and communication networks, in which one UAV maneuvers as the aerial dual-functional base-station (BS), while another UAV flies as the cooperative jammer. Artificial noise (AN) transmitted by the jamming UAV is utilized not only to confuse the ground warden but also to aid the aerial BS to sense multiple ground targets by combing the target-echoe…

Dynamic Strategy Adaptation in Multi-Agent Environments with Large Language Models
Shaurya Mallampati, Rashed Shelim, Walid Saad, Naren Ramakrishnan
https://arxiv.org/abs/2507.02002

Dynamic Strategy Adaptation in Multi-Agent Environments with Large Language Models
Large language models (LLMs) demonstrate strong reasoning abilities across mathematical, strategic, and linguistic tasks, yet little is known about how well they reason in dynamic, real-time, multi-agent scenarios, such as collaborative environments in which agents continuously adapt to each other's behavior, as in cooperative gameplay settings. In this paper, we bridge this gap by combining LLM-driven agents with strategic reasoning and real-time adaptation in cooperative, multi-agent environm…

Online Planning for Cooperative Air-Ground Robot Systems with Unknown Fuel Requirements
Ritvik Agarwal, Behnoushsadat Hatami, Alvika Gautam, Parikshit Maini
https://arxiv.org/abs/2506.20804

Online Planning for Cooperative Air-Ground Robot Systems with Unknown Fuel Requirements
We consider an online variant of the fuel-constrained UAV routing problem with a ground-based mobile refueling station (FCURP-MRS), where targets incur unknown fuel costs. We develop a two-phase solution: an offline heuristic-based planner computes initial UAV and UGV paths, and a novel online planning algorithm that dynamically adjusts rendezvous points based on real-time fuel consumption during target processing. Preliminary Gazebo simulations demonstrate the feasibility of our approach in ma…

Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework
Michael Ledford, William Regli
https://arxiv.org/abs/2506.15856 …

Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework
Cooperative multi-agent systems often face tasks that require coordinated actions under uncertainty. While multi-armed bandit (MAB) problems provide a powerful framework for decentralized learning, most prior work assumes individually attainable rewards. We address the challenging setting where rewards are threshold-activated: an arm yields a payoff only when a minimum number of agents pull it simultaneously, with this threshold unknown in advance. Complicating matters further, some arms are de…

Factor-Graph-Based Passive Acoustic Navigation for Decentralized Cooperative Localization Using Bearing Elevation Depth Difference
Kalliyan Velasco, Timothy W. McLain, Joshua G. Mangelson
https://arxiv.org/abs/2506.14690

Factor-Graph-Based Passive Acoustic Navigation for Decentralized Cooperative Localization Using Bearing Elevation Depth Difference
Accurate and scalable underwater multi-agent localization remains a critical challenge due to the constraints of underwater communication. In this work, we propose a multi-agent localization framework using a factor-graph representation that incorporates bearing, elevation, and depth difference (BEDD). Our method leverages inverted ultra-short baseline (inverted-USBL) derived azimuth and elevation measurements from incoming acoustic signals and relative depth measurements to enable cooperative …

Accuracy and Security-Guaranteed Participant Selection and Beamforming Design for RIS-Assisted Federated Learning
Mengru Wu, Yu Gao, Weidang Lu, Huimei Han, Lei Sun, Wanli Ni
https://arxiv.org/abs/2507.00388

Accuracy and Security-Guaranteed Participant Selection and Beamforming Design for RIS-Assisted Federated Learning
Federated learning (FL) has emerged as an effective approach for training neural network models without requiring the sharing of participants' raw data, thereby addressing data privacy concerns. In this paper, we propose a reconfigurable intelligent surface (RIS)-assisted FL framework in the presence of eavesdropping, where partial edge devices are selected to participate in the FL training process. In contrast, the remaining devices serve as cooperative jammers by transmitting jamming signals …

This https://arxiv.org/abs/2407.09206 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Cooperative Indoor Exploration Leveraging a Mixed-Size UAV Team with Heterogeneous Sensors
Heterogeneous teams of Unmanned Aerial Vehicles (UAVs) can enhance the exploration capabilities of aerial robots by exploiting different strengths and abilities of varying UAVs. This paper presents a novel method for exploring unknown indoor spaces with a team of UAVs of different sizes and sensory equipment. We propose a frontier-based exploration with two task allocation strategies: a greedy strategy that assigns Points of Interest (POIs) based on Euclidean distance and UAV priority and an op…

Conceal Truth while Show Fake: T/F Frequency Multiplexing based Anti-Intercepting Transmission
Zhisheng Yin, Nan Cheng, Tom H. Luan, Mingjie Wang, Dongbo Li, Yiliang Liu, Changle Li
https://arxiv.org/abs/2506.00811

Conceal Truth while Show Fake: T/F Frequency Multiplexing based Anti-Intercepting Transmission
In wireless communication adversarial scenarios, signals are easily intercepted by non-cooperative parties, exposing the transmission of confidential information. This paper proposes a true-and-false (T/F) frequency multiplexing based anti-intercepting transmission scheme capable of concealing truth while showing fake (CTSF), integrating both offensive and defensive strategies. Specifically, through multi-source cooperation, true and false signals are transmitted over multiple frequency bands u…

This https://arxiv.org/abs/2502.05808 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Positioning-Aided Channel Estimation for Multi-LEO Satellite Cooperative Communications
We investigate a multi-low Earth orbit (LEO) satellite system that simultaneously provides positioning and communication services to terrestrial user terminals. To address the challenges of channel estimation in LEO satellite systems, we propose a novel two-timescale positioning-aided channel estimation framework, exploiting the distinct variation rates of position-related parameters and channel gains inherent in LEO satellite channels. Using the misspecified Cramér-Rao bound (MCRB) theory, we…

Learning Bilateral Team Formation in Cooperative Multi-Agent Reinforcement Learning
Koorosh Moslemi, Chi-Guhn Lee
https://arxiv.org/abs/2506.20039 https://…

Learning Bilateral Team Formation in Cooperative Multi-Agent Reinforcement Learning
Team formation and the dynamics of team-based learning have drawn significant interest in the context of Multi-Agent Reinforcement Learning (MARL). However, existing studies primarily focus on unilateral groupings, predefined teams, or fixed-population settings, leaving the effects of algorithmic bilateral grouping choices in dynamic populations underexplored. To address this gap, we introduce a framework for learning two-sided team formation in dynamic multi-agent systems. Through this study, …

This https://arxiv.org/abs/2506.01538 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

LAMARL: LLM-Aided Multi-Agent Reinforcement Learning for Cooperative Policy Generation
Although Multi-Agent Reinforcement Learning (MARL) is effective for complex multi-robot tasks, it suffers from low sample efficiency and requires iterative manual reward tuning. Large Language Models (LLMs) have shown promise in single-robot settings, but their application in multi-robot systems remains largely unexplored. This paper introduces a novel LLM-Aided MARL (LAMARL) approach, which integrates MARL with LLMs, significantly enhancing sample efficiency without requiring manual design. LA…

Improving Multi-Vehicle Perception Fusion with Millimeter-Wave Radar Assistance
Zhiqing Luo, Yi Wang, Yingying He, Wei Wang
https://arxiv.org/abs/2506.00837

Improving Multi-Vehicle Perception Fusion with Millimeter-Wave Radar Assistance
Cooperative perception enables vehicles to share sensor readings and has become a new paradigm to improve driving safety, where the key enabling technology for realizing this vision is to real-time and accurately align and fuse the perceptions. Recent advances to align the views rely on high-density LiDAR data or fine-grained image feature representations, which however fail to meet the requirements of accuracy, real-time, and adaptability for autonomous driving. To this end, we present MMatch,…

Position and Velocity Estimation Accuracy in MIMO-OFDM ISAC Networks: A Fisher Information Analysis
Lorenzo Pucci, Luca Arcangeloni, Andrea Giorgetti
https://arxiv.org/abs/2507.01743

Position and Velocity Estimation Accuracy in MIMO-OFDM ISAC Networks: A Fisher Information Analysis
Integrated sensing and communication (ISAC) is a core technology for future wireless networks, enabling high-resolution sensing and reliable data transmission within a unified radio platform. This paper develops a theoretical framework to assess the estimation accuracy of target position and velocity in heterogeneous orthogonal frequency division multiplexing (OFDM)-based ISAC networks with multiple cooperative and distributed multiple-input multiple-output (MIMO) base stations (BSs). Using Fis…

CORA: Coalitional Rational Advantage Decomposition for Multi-Agent Policy Gradients
Mengda Ji, Genjiu Xu, Liying Wang
https://arxiv.org/abs/2506.04265 http…

CORA: Coalitional Rational Advantage Decomposition for Multi-Agent Policy Gradients
This work focuses on the credit assignment problem in cooperative multi-agent reinforcement learning (MARL). Sharing the global advantage among agents often leads to suboptimal policy updates as it fails to account for the distinct contributions of agents. Although numerous methods consider global or individual contributions for credit assignment, a detailed analysis at the coalition level remains lacking in many approaches. This work analyzes the over-updating problem during multi-agent policy…

This https://arxiv.org/abs/2505.20751 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Interactive OT Gym: A Reinforcement Learning-Based Interactive Optical tweezer (OT)-Driven Microrobotics Simulation Platform
Optical tweezers (OT) offer unparalleled capabilities for micromanipulation with submicron precision in biomedical applications. However, controlling conventional multi-trap OT to achieve cooperative manipulation of multiple complex-shaped microrobots in dynamic environments poses a significant challenge. To address this, we introduce Interactive OT Gym, a reinforcement learning (RL)-based simulation platform designed for OT-driven microrobotics. Our platform supports complex physical field sim…

This https://arxiv.org/abs/2411.13983 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csMA_…

Learning Two-agent Motion Planning Strategies from Generalized Nash Equilibrium for Model Predictive Control
We introduce an Implicit Game-Theoretic MPC (IGT-MPC), a decentralized algorithm for two-agent motion planning that uses a learned value function that predicts the game-theoretic interaction outcomes as the terminal cost-to-go function in a model predictive control (MPC) framework, guiding agents to implicitly account for interactions with other agents and maximize their reward. This approach applies to competitive and cooperative multi-agent motion planning problems which we formulate as const…

Thinking Beyond Visibility: A Near-Optimal Policy Framework for Locally Interdependent Multi-Agent MDPs
Alex DeWeese, Guannan Qu
https://arxiv.org/abs/2506.04215

Thinking Beyond Visibility: A Near-Optimal Policy Framework for Locally Interdependent Multi-Agent MDPs
Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs) are known to be NEXP-Complete and intractable to solve. However, for problems such as cooperative navigation, obstacle avoidance, and formation control, basic assumptions can be made about local visibility and local dependencies. The work DeWeese and Qu 2024 formalized these assumptions in the construction of the Locally Interdependent Multi-Agent MDP. In this setting, it establishes three closed-form policies that are tr…