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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 …

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…

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

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…

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 …

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

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…

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…

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…

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…

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…

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…

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…

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…

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…

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…

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…

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…