Tootfinder

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 …

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…

Co-Design of Sensing, Communications, and Control for Low-Altitude Wireless Networks
Haijia Jin, Jun Wu, Weijie Yuan, Fan Liu, Yuanhao Cui
https://arxiv.org/abs/2506.20970

Co-Design of Sensing, Communications, and Control for Low-Altitude Wireless Networks
The rapid advancement of Internet of Things (IoT) services and the evolution toward the sixth generation (6G) have positioned unmanned aerial vehicles (UAVs) as critical enablers of low-altitude wireless networks (LAWNs). This work investigates the co-design of integrated sensing, communication, and control ($\mathbf{SC^{2}}$) for multi-UAV cooperative systems with finite blocklength (FBL) transmission. In particular, the UAVs continuously monitor the state of the field robots and transmit thei…

Institutional Noise, Strategic Deviation, and Intertemporal Collapse: A Formal Model of Miner Behaviour under Protocol Uncertainty
Craig Steven Wright
https://arxiv.org/abs/2506.20992

Institutional Noise, Strategic Deviation, and Intertemporal Collapse: A Formal Model of Miner Behaviour under Protocol Uncertainty
This paper develops a formal game-theoretic model to examine how protocol mutability disrupts cooperative mining behaviour in blockchain systems. Using a repeated game framework with stochastic rule shocks, we show that even minor uncertainty in institutional rules increases time preference and induces strategic deviation. Fixed-rule environments support long-term investment and stable equilibrium strategies; in contrast, mutable protocols lead to short-termism, higher discounting, and collapse…

ChatChecker: A Framework for Dialogue System Testing and Evaluation Through Non-cooperative User Simulation
Roman Mayr, Michel Schimpf, Thomas Bohn\'e
https://arxiv.org/abs/2507.16792

ChatChecker: A Framework for Dialogue System Testing and Evaluation Through Non-cooperative User Simulation
While modern dialogue systems heavily rely on large language models (LLMs), their implementation often goes beyond pure LLM interaction. Developers integrate multiple LLMs, external tools, and databases. Therefore, assessment of the underlying LLM alone does not suffice, and the dialogue systems must be tested and evaluated as a whole. However, this remains a major challenge. With most previous work focusing on turn-level analysis, less attention has been paid to integrated dialogue-level quali…

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, …

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…

Quantum Machine Learning for Secure Cooperative Multi-Layer Edge AI with Proportional Fairness
Thai T. Vu, John Le
https://arxiv.org/abs/2507.15145 https:/…

Quantum Machine Learning for Secure Cooperative Multi-Layer Edge AI with Proportional Fairness
This paper proposes a communication-efficient, event-triggered inference framework for cooperative edge AI systems comprising multiple user devices and edge servers. Building upon dual-threshold early-exit strategies for rare-event detection, the proposed approach extends classical single-device inference to a distributed, multi-device setting while incorporating proportional fairness constraints across users. A joint optimization framework is formulated to maximize classification utility under…

Rational Miner Behaviour, Protocol Stability, and Time Preference: An Austrian and Game-Theoretic Analysis of Bitcoin's Incentive Environment
Craig Steven Wright
https://arxiv.org/abs/2506.20965

Rational Miner Behaviour, Protocol Stability, and Time Preference: An Austrian and Game-Theoretic Analysis of Bitcoin's Incentive Environment
This paper integrates Austrian capital theory with repeated game theory to examine strategic miner behaviour under different institutional conditions in blockchain systems. It shows that when protocol rules are mutable, effective time preference rises, undermining rational long-term planning and cooperative equilibria. Using formal game-theoretic analysis and Austrian economic principles, the paper demonstrates how mutable protocols shift miner incentives from productive investment to political…

Sensing-Aware Transmit Waveform/Receive Filter Design for OFDM-MBS Systems
Xinghe Li, Kainan Cheng, Huiyong Li, Huiyong Li, Ziyang Cheng
https://arxiv.org/abs/2506.20231

Sensing-Aware Transmit Waveform/Receive Filter Design for OFDM-MBS Systems
In this letter, we study the problem of cooperative sensing design for an orthogonal frequency division multiplexing (OFDM) multiple base stations (MBS) system. We consider a practical scenario where the base stations (BSs) exploit certain subcarriers to realize a sensing function. Since the high sidelobe level (SLL) of OFDM waveforms degrades radar detection for weak targets, and the cross-correlation generated by other BSs further exacerbates detection performance, we devise a joint design sc…

Fronthaul-Aware User-Centric Generalized Cell-Free Massive MIMO Systems
Zahra Mobini, Ahmet Hasim Gokceoglu, Li Wang, Gunnar Peters, Hien Quoc Ngo
https://arxiv.org/abs/2506.14494

Fronthaul-Aware User-Centric Generalized Cell-Free Massive MIMO Systems
We consider fronthaul-limited generalized zeroforcing-based cell-free massive multiple-input multiple-output (CF-mMIMO) systems with multiple-antenna users and multipleantenna access points (APs) relying on both cooperative beamforming (CB) and user-centric (UC) clustering. The proposed framework is very general and can be degenerated into different special cases, such as pure CB/pure UC clustering, or fully centralized CB/fully distributed beamforming. We comprehensively analyze the spectral e…

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…

Decentralized Consensus Inference-based Hierarchical Reinforcement Learning for Multi-Constrained UAV Pursuit-Evasion Game
Xiang Yuming, Li Sizhao, Li Rongpeng, Zhao Zhifeng, Zhang Honggang
https://arxiv.org/abs/2506.18126

Decentralized Consensus Inference-based Hierarchical Reinforcement Learning for Multi-Constrained UAV Pursuit-Evasion Game
Multiple quadrotor unmanned aerial vehicle (UAV) systems have garnered widespread research interest and fostered tremendous interesting applications, especially in multi-constrained pursuit-evasion games (MC-PEG). The Cooperative Evasion and Formation Coverage (CEFC) task, where the UAV swarm aims to maximize formation coverage across multiple target zones while collaboratively evading predators, belongs to one of the most challenging issues in MC-PEG, especially under communication-limited con…

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…

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…

Segregation and cooperation in active colloidal binary mixtures
Laura Alvarez, Elena Ses\'e-Sansa, Demian Levis, Ignacio Pagonabarraga, Lucio Isa
https://arxiv.org/abs/2506.15188

Segregation and cooperation in active colloidal binary mixtures
The complex interactions underlying collective motion in biological systems give rise to emergent behaviours such as flocking, sorting, and cooperative transport. These dynamics often involve species with different motilities coordinating movement to optimize navigation and survival. Synthetic analogues based on active colloids offer a controlled platform to explore such behaviours, yet most experimental realizations remain limited to monodisperse systems or mixtures of passive and active parti…

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…

Local Differential Privacy for Distributed Stochastic Aggregative Optimization with Guaranteed Optimality
Ziqin Chen, Yongqiang Wang
https://arxiv.org/abs/2506.15106

Local Differential Privacy for Distributed Stochastic Aggregative Optimization with Guaranteed Optimality
Distributed aggregative optimization underpins many cooperative optimization and multi-agent control systems, where each agent's objective function depends both on its local optimization variable and an aggregate of all agents' optimization variables. Existing distributed aggregative optimization approaches typically require access to accurate gradients of the objective functions, which, however, are often hard to obtain in real-world applications. For example, in machine learning, gradients ar…

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…

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…

New allocation rule based on graph structures and their application to economic phenomena
Taiki Yamada, Taisuke Matsubae, Tomoya Akamatsu
https://arxiv.org/abs/2507.11808

New allocation rule based on graph structures and their application to economic phenomena
This study introduces the \emph{edge-based Shapley value}, a novel allocation rule within cooperative game theory, specifically tailored for networked systems, where value is generated through interactions represented by edges. Traditional allocation rules, such as the Shapley and Myerson values, evaluate player contributions based on node-level characteristics, or connected components. However, these approaches often fail to adequately capture the functional role of edges, which are crucial in…

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…

"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.

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…

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…

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…

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,…

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…

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…

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…

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 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…

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…

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…

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

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…

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…

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…

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…