Tootfinder

MARCO: A Cooperative Knowledge Transfer Framework for Personalized Cross-domain Recommendations
Lili Xie, Yi Zhang, Ruihong Qiu, Jiajun Liu, Sen Wang
https://arxiv.org/abs/2510.04508

MARCO: A Cooperative Knowledge Transfer Framework for Personalized Cross-domain Recommendations
Recommender systems frequently encounter data sparsity issues, particularly when addressing cold-start scenarios involving new users or items. Multi-source cross-domain recommendation (CDR) addresses these challenges by transferring valuable knowledge from multiple source domains to enhance recommendations in a target domain. However, existing reinforcement learning (RL)-based CDR methods typically rely on a single-agent framework, leading to negative transfer issues caused by inconsistent doma…

Cooperative Flexibility Exchange: Fair and Comfort-Aware Decentralized Resource Allocation
Rabiya Khalid, Evangelos Pournaras
https://arxiv.org/abs/2510.04192 https://

Cooperative Flexibility Exchange: Fair and Comfort-Aware Decentralized Resource Allocation
The growing electricity demand and increased use of smart appliances are placing new pressures on power grids, making efficient energy management more important than ever. The existing energy management systems often prioritize system efficiency (balanced energy demand and supply) at the expense of user comfort. This paper addresses this gap by proposing a novel decentralized multi-agent coordination-based demand-side management system. The proposed system enables individual agents to coordinat…

Joint Probing and Scheduling for Cache-Aided Hybrid Satellite-Terrestrial Networks
Zhou Zhang, Yizhu Wang, Saman Atapattu, Sumei Sun
https://arxiv.org/abs/2510.04492 https://

Joint Probing and Scheduling for Cache-Aided Hybrid Satellite-Terrestrial Networks
Caching is crucial in hybrid satellite-terrestrial networks to reduce latency, optimize throughput, and improve data availability by storing frequently accessed content closer to users, especially in bandwidth-limited satellite systems, requiring strategic Medium Access Control (MAC) layer. This paper addresses throughput optimization in satellite-terrestrial integrated networks through opportunistic cooperative caching. We propose a joint probing and scheduling strategy to enhance content retr…

Learning to Lead Themselves: Agentic AI in MAS using MARL
Ansh Kamthan
https://arxiv.org/abs/2510.00022 https://arxiv.org/pdf/2510.00022

Learning to Lead Themselves: Agentic AI in MAS using MARL
As autonomous systems move from prototypes to real deployments, the ability of multiple agents to make decentralized, cooperative decisions becomes a core requirement. This paper examines how agentic artificial intelligence, agents that act independently, adaptively and proactively can improve task allocation and coordination in multi-agent systems, with primary emphasis on drone delivery and secondary relevance to warehouse automation. We formulate the problem in a cooperative multi-agent rein…

Cooperative Multi-Agent Path Planning for Heterogeneous UAVs in Contested Environments
Grant Stagg, Cameron K. Peterson
https://arxiv.org/abs/2509.02483 https://

Cooperative Multi-Agent Path Planning for Heterogeneous UAVs in Contested Environments
This paper addresses the challenge of navigating unmanned aerial vehicles in contested environments by introducing a cooperative multi-agent framework that increases the likelihood of safe UAV traversal. The approach involves two types of UAVs: low-priority agents that explore and localize threats, and a high-priority agent that navigates safely to its target destination while minimizing the risk of detection by enemy radar systems. The low-priority agents employ a decentralized optimization al…

A Novel Coded Caching Scheme for Partially Cooperative Device-to-Device Networks
Rashid Ummer N. T., K. K. Krishnan Namboodiri, B. Sundar Rajan
https://arxiv.org/abs/2509.02532 …

A Novel Coded Caching Scheme for Partially Cooperative Device-to-Device Networks
Device-to-device (D2D) communication is one of the most promising techniques for future wireless cellular communication systems. This paper considers coded caching in a partially cooperative wireless D2D network, where only a subset of users transmit during delivery, while all users request files. The non-transmitting users are referred to as selfish users. All existing schemes that do not require knowledge of the identity of selfish users before content placement are limited to the high-memory…

Cooperative Guidance for Aerial Defense in Multiagent Systems
Shivam Bajpai, Abhinav Sinha, Shashi Ranjan Kumar
https://arxiv.org/abs/2510.02087 https://ar…

Cooperative Guidance for Aerial Defense in Multiagent Systems
This paper addresses a critical aerial defense challenge in contested airspace, involving three autonomous aerial vehicles -- a hostile drone (the pursuer), a high-value drone (the evader), and a protective drone (the defender). We present a cooperative guidance framework for the evader-defender team that guarantees interception of the pursuer before it can capture the evader, even under highly dynamic and uncertain engagement conditions. Unlike traditional heuristic, optimal control, or differ…

Methodology for Test Case Allocation based on a Formalized ODD
Martin Skoglund, Fredrik Warg, Anders Thoren, Sasikumar Punnekkat, Hans Hansson
https://arxiv.org/abs/2509.02311 h…

Methodology for Test Case Allocation based on a Formalized ODD
The emergence of Connected, Cooperative, and Automated Mobility (CCAM) systems has significantly transformed the safety assessment landscape. Because they integrate automated vehicle functions beyond those managed by a human driver, new methods are required to evaluate their safety. Approaches that compile evidence from multiple test environments have been proposed for type-approval and similar evaluations, emphasizing scenario coverage within the systems Operational Design Domain (ODD). Howeve…

Q-Learning--Driven Adaptive Rewiring for Cooperative Control in Heterogeneous Networks
Yi-Ning Weng, Hsuan-Wei Lee
https://arxiv.org/abs/2509.01057 https://

Q-Learning--Driven Adaptive Rewiring for Cooperative Control in Heterogeneous Networks
Cooperation emergence in multi-agent systems represents a fundamental statistical physics problem where microscopic learning rules drive macroscopic collective behavior transitions. We propose a Q-learning-based variant of adaptive rewiring that builds on mechanisms studied in the literature. This method combines temporal difference learning with network restructuring so that agents can optimize strategies and social connections based on interaction histories. Through neighbor-specific Q-learni…

Crosslisted article(s) found for cs.MA. https://arxiv.org/list/cs.MA/new
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- Cooperative Grasping for Collective Object Transport in Constrained Environments
David Alvear, George Turkiyyah, Shinkyu Park

Energy-Efficient Precoding for Dense VCSEL-Based OWC Systems Under a Cooperative Broadcast Model
Hossein Safi, Asim Ihsan, Hossien B. Eldeeb, Bastien Bechadergue, Iman Tavakkolnia, Harald Haas
https://arxiv.org/abs/2508.18871

Energy-Efficient Precoding for Dense VCSEL-Based OWC Systems Under a Cooperative Broadcast Model
As 6G and beyond aim for sustainable, high-capacity wireless connectivity, optical wireless communication (OWC) has emerged as a compelling solution.Recent advances in vertical-cavity surface-emitting laser (VCSEL) arrays have significantly enhanced OWC performance, enabling high-speed, low-power data transmission. However, dense VCSEL deployments introduce challenges related to interference and energy efficiency (EE). This paper proposes a scalable precoding framework for EE maximization in fu…

Least Energy Solutions for Cooperative and Competitive Schr\"odinger Systems with Neumann Boundary Conditions
Simone Mauro, Delia Schiera, Hugo Tavares
https://arxiv.org/abs/2509.18835

Least Energy Solutions for Cooperative and Competitive Schrödinger Systems with Neumann Boundary Conditions
We study the following gradient elliptic system with Neumann boundary conditions \begin{equation*} -Δu + λ_1 u = u^3 + βuv^2, \ -Δv + λ_2 v = v^3 + βu^2 v \ \text{in } Ω,\qquad \frac{\partial u}{\partial ν} = \frac{\partial v}{\partial ν} = 0 \ \text{on } \partial Ω, \end{equation*} where $Ω\subset \mathbb{R}^N $ is a bounded $ C^2$ domain with $ N \leq 4 $, and $ ν$ denotes the outward unit normal on the boundary. We investigate the existence of non-constant least energy solutions …

Cooperative Sensing-Assisted Predictive Beam Tracking for MIMO-OFDM Networked ISAC Systems
Xiaoyu Yang, Zhiqing Wei, Jie Xu, Huici Wu, Zhiyong Feng
https://arxiv.org/abs/2508.12723

Cooperative Sensing-Assisted Predictive Beam Tracking for MIMO-OFDM Networked ISAC Systems
This paper studies a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) networked integrated sensing and communication (ISAC) system, in which multiple base stations (BSs) perform beam tracking to communicate with a mobile device. In particular, we focus on the beam tracking over a number of tracking time slots (TTSs) and suppose that these BSs operate at non-overlapping frequency bands to avoid the severe inter-cell interference. Under this setup, we propos…

Application Management in C-ITS: Orchestrating Demand-Driven Deployments and Reconfigurations
Lukas Zanger, Bastian Lampe, Lennart Reiher, Lutz Eckstein
https://arxiv.org/abs/2509.18793

Application Management in C-ITS: Orchestrating Demand-Driven Deployments and Reconfigurations
Vehicles are becoming increasingly automated and interconnected, enabling the formation of cooperative intelligent transport systems (C-ITS) and the use of offboard services. As a result, cloud-native techniques, such as microservices and container orchestration, play an increasingly important role in their operation. However, orchestrating applications in a large-scale C-ITS poses unique challenges due to the dynamic nature of the environment and the need for efficient resource utilization. In…

Design Insights and Comparative Evaluation of a Hardware-Based Cooperative Perception Architecture for Lane Change Prediction
Mohamed Manzour, Catherine M. Elias, Omar M. Shehata, Rub\'en Izquierdo, Miguel \'Angel Sotelo
https://arxiv.org/abs/2509.20218

Design Insights and Comparative Evaluation of a Hardware-Based Cooperative Perception Architecture for Lane Change Prediction
Research on lane change prediction has gained attention in the last few years. Most existing works in this area have been conducted in simulation environments or with pre-recorded datasets, these works often rely on simplified assumptions about sensing, communication, and traffic behavior that do not always hold in practice. Real-world deployments of lane-change prediction systems are relatively rare, and when they are reported, the practical challenges, limitations, and lessons learned are oft…

Trajectory Encryption Cooperative Salvo Guidance
Lohitvel Gopikannan, Shashi Ranjan Kumar, Abhinav Sinha
https://arxiv.org/abs/2509.17341 https://arxiv.org…

Trajectory Encryption Cooperative Salvo Guidance
This paper introduces the concept of trajectory encryption in cooperative simultaneous target interception, wherein heterogeneity in guidance principles across a team of unmanned autonomous systems is leveraged as a strategic design feature. By employing a mix of heterogeneous time-to-go formulations leading to a cooperative guidance strategy, the swarm of vehicles is able to generate diverse trajectory families. This diversity expands the feasible solution space for simultaneous target interce…

Superradiance and Superabsorption Engine of $N$ Two-Level Systems: $N^{2}$-Power Scaling at Near-Unity Efficiency
L. F. Alves da Silva, H. Sanchez, M. A. Ponte, M. H. Y. Moussa, Norton G. de Almeida
https://arxiv.org/abs/2510.12017

Superradiance and Superabsorption Engine of $N$ Two-Level Systems: $N^{2}$-Power Scaling at Near-Unity Efficiency
We present a thermal engine that exploits the \emph{cooperative superradiance} and \emph{superabsorption} of a sample of \(N\) two-level atoms. This engine operates using a single cold reservoir via cycles of collective pumping followed by decay. Using an effective mean-field Hamiltonian to describe the many-body dynamics, we design optimized drive pulses that preserve adiabaticity and achieve an average power output scaling quadratically with the system size, \(P \propto N^2\). An experimental…

Reinforced dynamics for interacting agents in competitive or cooperative environments
Michele Aleandri, Paolo Dai Pra, Ida Germana Minelli
https://arxiv.org/abs/2509.13493 https…

Reinforced dynamics for interacting agents in competitive or cooperative environments
We study systems of interacting reinforced stochastic processes, where agents' decisions evolve under reinforcement, network-mediated interactions, and environmental influences. In competitive environments with irreducible networks, we prove almost sure convergence of agents' states, with bipartite graphs leading to non-deterministic limits and non-bipartite graphs to deterministic ones. These results are extended to reducible networks with cooperative or competitive substructures, using a hier…

Design Insights and Comparative Evaluation of a Hardware-Based Cooperative Perception Architecture for Lane Change Prediction
Mohamed Manzour, Catherine M. Elias, Omar M. Shehata, Rub\'en Izquierdo, Miguel \'Angel Sotelo
https://arxiv.org/abs/2509.20218

Design Insights and Comparative Evaluation of a Hardware-Based Cooperative Perception Architecture for Lane Change Prediction
Research on lane change prediction has gained attention in the last few years. Most existing works in this area have been conducted in simulation environments or with pre-recorded datasets, these works often rely on simplified assumptions about sensing, communication, and traffic behavior that do not always hold in practice. Real-world deployments of lane-change prediction systems are relatively rare, and when they are reported, the practical challenges, limitations, and lessons learned are oft…

Co-Investment with Payoff-Sharing Mechanism for Cooperative Decision-Making in Network Design Games
Mingjia He, Andrea Censi, Emilio Frazzoli, Gioele Zardini
https://arxiv.org/abs/2508.12059

Co-Investment with Payoff-Sharing Mechanism for Cooperative Decision-Making in Network Design Games
Network-based systems are inherently interconnected, with the design and performance of subnetworks being interdependent. However, the decisions of self-interested operators may lead to suboptimal outcomes for users and the overall system. This paper explores cooperative mechanisms that can simultaneously benefit both operators and users. We address this challenge using a game-theoretical framework that integrates both non-cooperative and cooperative game theory. In the non-cooperative stage, w…

Dairy Farmers of America confirms June cyberattack leaked personal data https://therecord.media/dairy-farm-leaked-info-ransomware

Evolution of Coordination Through Institutional Incentives: An Evolutionary Game Theory Approach
Ndidi Bianca Ogbo, Zhao Song, The Anh Han
https://arxiv.org/abs/2509.10112 https…

Evolution of Coordination Through Institutional Incentives: An Evolutionary Game Theory Approach
There is a broad recognition that commitment-based mechanisms can promote coordination and cooperative behaviours in both biological populations and self-organised multi-agent systems by making individuals' intentions explicit prior to engagement. Yet their effectiveness depends on sustained compliance supported by institutions, especially in one-off interactions. Despite advances in quantitative studies of cooperation and commitment, most applied analyses and policy debates remain largely qual…

Towards Hybrid Lunar PNT: Error Models, Lower Bounds and Algorithms
Robert P\"ohlmann, Emanuel Staudinger, Gonzalo Seco-Granados
https://arxiv.org/abs/2508.10699 https://…

Towards Hybrid Lunar PNT: Error Models, Lower Bounds and Algorithms
Accurate positioning, navigation and timing (PNT) are crucial for upcoming lunar surface missions. Lunar satellite navigation systems are being developed, but lack coverage during early deployment phases. Hybrid lunar PNT combining cooperative navigation, satellite systems, and an optional reference station offers improved accuracy and availability. This study develops realistic error models that incorporate temporal correlations often ignored in existing works. We derive a cooperative navigati…

Empirical Study on Robustness and Resilience in Cooperative Multi-Agent Reinforcement Learning
Simin Li, Zihao Mao, Hanxiao Li, Zonglei Jing, Zhuohang bian, Jun Guo, Li Wang, Zhuoran Han, Ruixiao Xu, Xin Yu, Chengdong Ma, Yuqing Ma, Bo An, Yaodong Yang, Weifeng Lv, Xianglong Liu
https://arxiv.org/abs/2510.11824

Empirical Study on Robustness and Resilience in Cooperative Multi-Agent Reinforcement Learning
In cooperative Multi-Agent Reinforcement Learning (MARL), it is a common practice to tune hyperparameters in ideal simulated environments to maximize cooperative performance. However, policies tuned for cooperation often fail to maintain robustness and resilience under real-world uncertainties. Building trustworthy MARL systems requires a deep understanding of robustness, which ensures stability under uncertainties, and resilience, the ability to recover from disruptions--a concept extensively …

Nonlinear Public Goods Game in Dynamical Environments
Yishen Jiang, Xin Wang, Wenqiang Zhu, Ming Wei, Longzhao Liu, Shaoting Tang, Hongwei Zheng
https://arxiv.org/abs/2510.10259

Nonlinear Public Goods Game in Dynamical Environments
The evolutionary mechanisms of cooperative behavior represent a fundamental topic in complex systems and evolutionary dynamics. Although recent advances have introduced real-world stochasticity in nonlinear public goods game (PGG), such stochasticity remains static, neglecting its origin in the external environment as well as the coevolution of system stochasticity and cooperative behavior driven by environmental dynamics. In this work, we introduce a dynamic environment feedback mechanism into…

Resilient Global Practical Fixed-Time Cooperative Output Regulation of Uncertain Nonlinear Multi-Agent Systems Subject to Denial-of-Service Attacks
Wenji Cao, Lu Liu, Zehua Ye, Dan Zhang, Gang Feng
https://arxiv.org/abs/2509.08324

Resilient Global Practical Fixed-Time Cooperative Output Regulation of Uncertain Nonlinear Multi-Agent Systems Subject to Denial-of-Service Attacks
This paper investigates the problem of resilient global practical fixed-time cooperative output regulation of uncertain nonlinear multi-agent systems subject to denial-of-service attacks. A novel distributed resilient adaptive fixed-time control strategy is proposed, which consists of a novel distributed resilient fixed-time observer with a chain of nonlinear filters and a novel distributed resilient adaptive fixed-time controller. It is shown that the problem of resilient global practical fixe…

Adaptive Semantic Communication for UAV/UGV Cooperative Path Planning
Fangzhou Zhao, Yao Sun, Jianglin Lan, Lan Zhang, Xuesong Liu, Muhammad Ali Imran
https://arxiv.org/abs/2510.06901

Adaptive Semantic Communication for UAV/UGV Cooperative Path Planning
Effective path planning is fundamental to the coordination of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems, particularly in applications such as surveillance, navigation, and emergency response. Combining UAVs' broad field of view with UGVs' ground-level operational capability greatly improve the likelihood of successfully achieving task objectives such as locating victims, monitoring target areas, or navigating hazardous terrain. In complex environments, UAVs nee…

An AUTOSAR-Aligned Architectural Study of Vulnerabilities in Automotive SoC Software
Srijita Basu, Haraldsson Bengt, Miroslaw Staron, Christian Berger, Jennifer Horkoff, Magnus Almgren
https://arxiv.org/abs/2510.07941

An AUTOSAR-Aligned Architectural Study of Vulnerabilities in Automotive SoC Software
Cooperative, Connected and Automated Mobility (CCAM) are complex cyber-physical systems (CPS) that integrate computation, communication, and control in safety-critical environments. At their core, System-on-Chip (SoC) platforms consolidate processing units, communication interfaces, AI accelerators, and security modules into a single chip. AUTOSAR (AUTomotive Open System ARchitecture) standard was developed in the automotive domain to better manage this complexity, defining layered software str…

Beyond the high score: Prosocial ability profiles of multi-agent populations
Marko Tesic, Yue Zhao, Joel Z. Leibo, Rakshit S. Trivedi, Jose Hernandez-Orallo
https://arxiv.org/abs/2509.14485

Beyond the high score: Prosocial ability profiles of multi-agent populations
The development and evaluation of social capabilities in AI agents require complex environments where competitive and cooperative behaviours naturally emerge. While game-theoretic properties can explain why certain teams or agent populations outperform others, more abstract behaviours, such as convention following, are harder to control in training and evaluation settings. The Melting Pot contest is a social AI evaluation suite designed to assess the cooperation capabilities of AI systems. In t…

Decentralized CBF-based Safety Filters for Collision Avoidance of Cooperative Missile Systems with Input Constraints
Johannes Autenrieb, Mark Spiller
https://arxiv.org/abs/2510.06846

Decentralized CBF-based Safety Filters for Collision Avoidance of Cooperative Missile Systems with Input Constraints
This paper presents a decentralized safety filter for collision avoidance in multi-agent aerospace interception scenarios. The approach leverages robust control barrier functions (RCBFs) to guarantee forward invariance of safety sets under bounded inputs and high-relative-degree dynamics. Each effector executes its nominal cooperative guidance command, while a local quadratic program (QP) modifies the input only when necessary. Event-triggered activation based on range and zero-effort miss (ZEM…

Structured Cooperative Multi-Agent Reinforcement Learning: a Bayesian Network Perspective
Shahbaz P Qadri Syed, He Bai
https://arxiv.org/abs/2510.09937 https://

Structured Cooperative Multi-Agent Reinforcement Learning: a Bayesian Network Perspective
The empirical success of multi-agent reinforcement learning (MARL) has motivated the search for more efficient and scalable algorithms for large scale multi-agent systems. However, existing state-of-the-art algorithms do not fully exploit inter-agent coupling information to develop MARL algorithms. In this paper, we propose a systematic approach to leverage structures in the inter-agent couplings for efficient model-free reinforcement learning. We model the cooperative MARL problem via a Bayesi…

Fully Distributed State Estimation for Multi-agent Systems and its Application in Cooperative Localization
Shuaiting Huang, Haodong Jiang, Chengcheng Zhao, Peng Cheng, Junfeng Wu
https://arxiv.org/abs/2509.18292

XAgents: A Unified Framework for Multi-Agent Cooperation via IF-THEN Rules and Multipolar Task Processing Graph
Hailong Yang, Mingxian Gu, Jianqi Wang, Guanjin Wang, Zhaohong Deng
https://arxiv.org/abs/2509.10054

XAgents: A Unified Framework for Multi-Agent Cooperation via IF-THEN Rules and Multipolar Task Processing Graph
The rapid advancement of Large Language Models (LLMs) has significantly enhanced the capabilities of Multi-Agent Systems (MAS) in supporting humans with complex, real-world tasks. However, MAS still face challenges in effective task planning when handling highly complex tasks with uncertainty, often resulting in misleading or incorrect outputs that hinder task execution. To address this, we propose XAgents, a unified multi-agent cooperative framework built on a multipolar task processing graph …

Optimal Real-time Communication in 6G Ultra-Massive V2X Mobile Networks
He Huang, Zilong Liu, Zeping Sui, Wei Huang, Md. Noor-A-Rahim, Haishi Wang, Zhiheng Hu
https://arxiv.org/abs/2510.06937

Optimal Real-time Communication in 6G Ultra-Massive V2X Mobile Networks
This paper introduces a novel cooperative vehicular communication algorithm tailored for future 6G ultra-massive vehicle-to-everything (V2X) networks leveraging integrated space-air-ground communication systems. Specifically, we address the challenge of real-time information exchange among rapidly moving vehicles. We demonstrate the existence of an upper bound on channel capacity given a fixed number of relays, and propose a low-complexity relay selection heuristic algorithm. Simulation results…

SafeDiver: Cooperative AUV-USV Assisted Diver Communication via Multi-agent Reinforcement Learning Approach
Tinglong Deng, Hang Tao, Xinxiang Wang, Yinyan Wang, Hanjiang Luo
https://arxiv.org/abs/2509.11508

SafeDiver: Cooperative AUV-USV Assisted Diver Communication via Multi-agent Reinforcement Learning Approach
As underwater human activities are increasing, the demand for underwater communication service presents a significant challenge. Existing underwater diver communication methods face hurdles due to inherent disadvantages and complex underwater environments. To address this issue, we propose a scheme that utilizes maritime unmanned systems to assist divers with reliable and high-speed communication. Multiple AUVs are equipped with optical and acoustic multimodal communication devices as relay nod…

Mediator-Guided Multi-Agent Collaboration among Open-Source Models for Medical Decision-Making
Kaitao Chen, Mianxin Liu, Daoming Zong, Chaoyue Ding, Shaohao Rui, Yankai Jiang, Mu Zhou, Xiaosong Wang
https://arxiv.org/abs/2508.05996

Mediator-Guided Multi-Agent Collaboration among Open-Source Models for Medical Decision-Making
Complex medical decision-making involves cooperative workflows operated by different clinicians. Designing AI multi-agent systems can expedite and augment human-level clinical decision-making. Existing multi-agent researches primarily focus on language-only tasks, yet their extension to multimodal scenarios remains challenging. A blind combination of diverse vision-language models (VLMs) can amplify an erroneous outcome interpretation. VLMs in general are less capable in instruction following a…

Three-state coevolutionary game dynamics with environmental feedback
Yi-Duo Chen, Zhi-Xi Wu, Jian-Yue Guan
https://arxiv.org/abs/2510.07946 https://arxiv.o…

Three-state coevolutionary game dynamics with environmental feedback
Environmental feedback mechanisms are ubiquitous in real-world complex systems. In this study, we incorporate a homogeneous environment into the evolutionary dynamics of a three-state system comprising cooperators, defectors, and empty nodes. Both coherence resonance and equilibrium states, resulting from the tightly clustering of cooperator agglomerates, enhance population survival and environmental quality. The resonance phenomenon arises at the transition between cooperative and defective pa…

Adaptive Evolutionary Framework for Safe, Efficient, and Cooperative Autonomous Vehicle Interactions
Zhen Tian, Zhihao Lin
https://arxiv.org/abs/2509.07411 https://

Adaptive Evolutionary Framework for Safe, Efficient, and Cooperative Autonomous Vehicle Interactions
Modern transportation systems face significant challenges in ensuring road safety, given serious injuries caused by road accidents. The rapid growth of autonomous vehicles (AVs) has prompted new traffic designs that aim to optimize interactions among AVs. However, effective interactions between AVs remains challenging due to the absence of centralized control. Besides, there is a need for balancing multiple factors, including passenger demands and overall traffic efficiency. Traditional rule-ba…