Tootfinder

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…

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 …

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…

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…

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…

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…

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…

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…

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…

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…

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…

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'…

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…

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…

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…

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…

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…

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…

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 …

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

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.

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…

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…

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 …

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…

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…

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…

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

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…

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…

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…

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…

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…

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…

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…

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…

Learning Recommender Mechanisms for Bayesian Stochastic Games
Bengisu Guresti, Chongjie Zhang, Yevgeniy Vorobeychik
https://arxiv.org/abs/2505.22979 https:…

Learning Recommender Mechanisms for Bayesian Stochastic Games
An important challenge in non-cooperative game theory is coordinating on a single (approximate) equilibrium from many possibilities - a challenge that becomes even more complex when players hold private information. Recommender mechanisms tackle this problem by recommending strategies to players based on their reported type profiles. A key consideration in such mechanisms is to ensure that players are incentivized to participate, report their private information truthfully, and follow the recom…

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/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…

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…

An operatorial view of competition and cooperation in a network of economic agents
G. Giunta, M. Gorgone, F. Oliveri
https://arxiv.org/abs/2505.22917 https…

An operatorial view of competition and cooperation in a network of economic agents
A network of agents interacting both with competitive and/or cooperative mechanisms is modeled by using fermionic ladder operators. The time evolution of the network is assumed to be governed by a Hermitian time-independent Hamiltonian operator, and the mean values of the number operators are interpreted as a measure of the wealth status of the agents. Besides classical Heisenberg, we use the recently introduced $(H,ρ)$-induced dynamics approach to account for some actions able to provide a se…

Phase transitions in the Prisoner's Dilemma game on the Barab\'asi-Albert graph with participation cost
Jacek Mi\c{e}kisz, Javad Mohamadichamgavi
https://arxiv.org/abs/2505.23370

Phase transitions in the Prisoner's Dilemma game on the Barabási-Albert graph with participation cost
We examine the impact of the maintenance cost of social links on cooperative behavior in the Prisoner's Dilemma game on the Barabási-Albert scale-free network with a pairwise stochastic imitation. We show by means of Monte Carlo simulations and pair approximation that the cooperation frequency changes abruptly from an almost full cooperation to a much smaller value when we increase the cost of maintaining links. In the critical region, the stationary distribution is bi-modal and the system osc…

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,…

This https://arxiv.org/abs/2501.08512 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csMA_…

Ensuring Truthfulness in Distributed Aggregative Optimization
Distributed aggregative optimization methods are gaining increased traction due to their ability to address cooperative control and optimization problems, where the objective function of each agent depends not only on its own decision variable but also on the aggregation of other agents' decision variables. Nevertheless, existing distributed aggregative optimization methods implicitly assume all agents to be truthful in information sharing, which can be unrealistic in real-world scenarios, wher…

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/2502.06976 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csMA_…

Who is Helping Whom? Analyzing Inter-dependencies to Evaluate Cooperation in Human-AI Teaming
State-of-the-art methods for Human-AI Teaming and Zero-shot Cooperation focus on task completion, i.e., task rewards, as the sole evaluation metric while being agnostic to how the two agents work with each other. Furthermore, subjective user studies only offer limited insight into the quality of cooperation existing within the team. Specifically, we are interested in understanding the cooperative behaviors arising within the team when trained agents are paired with humans -- a problem that has …