Tootfinder

https://socket.dev/blog/gem-cooperative-emerges-as-a-community-run-alternative-to-rubygems-org

A Robust Cooperative Vehicle Coordination Framework for Intersection Crossing
Haojie Bai, Jiping Luo, Huafu Li, Xiongwei Zhao, Yang Wang
https://arxiv.org/abs/2508.03417 https:/…

A Robust Cooperative Vehicle Coordination Framework for Intersection Crossing
Cooperative vehicle coordination at unsignalized intersections has garnered significant interest from both academia and industry in recent years, highlighting its notable advantages in improving traffic throughput and fuel efficiency. However, most existing studies oversimplify the coordination system, assuming accurate vehicle state information and ideal state update process. The oversights pose driving risks in the presence of state uncertainty and communication constraint. To address this ga…

Engineered over Emergent Communication in MARL for Scalable and Sample-Efficient Cooperative Task Allocation in a Partially Observable Grid
Brennen A. Hill, Mant Koh En Wei, Thangavel Jishnuanandh
https://arxiv.org/abs/2508.02912

Engineered over Emergent Communication in MARL for Scalable and Sample-Efficient Cooperative Task Allocation in a Partially Observable Grid
We compare the efficacy of learned versus engineered communication strategies in a cooperative multi-agent reinforcement learning (MARL) environment. For the learned approach, we introduce Learned Direct Communication (LDC), where agents generate messages and actions concurrently via a neural network. Our engineered approach, Intention Communication, employs an Imagined Trajectory Generation Module (ITGM) and a Message Generation Network (MGN) to formulate messages based on predicted future sta…

About a month ago I was a bit too optimistic*, the admin took over a month to complete....: Only last Tuesday Reasonable Sourcery was officially inCOOPerated.
Today we finally sent out the official introduction:
<https://lists.gnu.org/archive/html/guix-devel/2025…

Multi-robot Rigid Formation Navigation via Synchronous Motion and Discrete-time Communication-Control Optimization
Qun Yang, Soung Chang Liew
https://arxiv.org/abs/2510.02624 ht…

Multi-robot Rigid Formation Navigation via Synchronous Motion and Discrete-time Communication-Control Optimization
Rigid-formation navigation of multiple robots is essential for applications such as cooperative transportation. This process involves a team of collaborative robots maintaining a predefined geometric configuration, such as a square, while in motion. For untethered collaborative motion, inter-robot communication must be conducted through a wireless network. Notably, few existing works offer a comprehensive solution for multi-robot formation navigation executable on microprocessor platforms via w…

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…

A Linear Programming Approach to Estimate the Core in Cooperative Games
J Camacho, JC Gon\c{c}alves-Dosantos, J S\'anchez-Soriano
https://arxiv.org/abs/2510.01766 https://…

A Linear Programming Approach to Estimate the Core in Cooperative Games
This paper proposes a novel algorithm to approximate the core of transferable utility (TU) cooperative games via linear programming. Given the computational hardness of determining the full core, our approach provides a tractable approximation by sampling extreme points through randomized linear problems (LPs). We analyze its convergence and computational complexity, and validate its effectiveness through extensive simulations on various game models. Our results show that the method is scalable…

The new USGS Cooperative National Geologic Map web tool was designed to also be mobile friendly,
allowing users to explore geologic data from smartphones and tablets, in addition to larger devices
https://ngmdb.usgs.gov/nationalgeology

Cooperative National Geologic Map | NGMDB
Explore the Cooperative National Geologic Map, a unified view of our Nation's geology, with interactive layers and geologic data.

The #Japan #media #cooperative, @…, I've been working with for 2 y…

A Group Consensus-Driven Auction Algorithm for Cooperative Task Allocation Among Heterogeneous Multi-Agents
Gang Wang, Hongfang Han, Xiaowei Liu, Hanfeng Jiang, Ming Zhang
https://arxiv.org/abs/2508.02015

A Group Consensus-Driven Auction Algorithm for Cooperative Task Allocation Among Heterogeneous Multi-Agents
In scenarios like automated warehouses, assigning tasks to robots presents a heterogeneous multi-task and multi-agent task allocation problem. However, existing task allocation study ignores the integration of multi-task and multi-attribute agent task allocation with heterogeneous task allocation. In addition, current algorithms are limited by scenario constraints and can incur significant errors in specific contexts. Therefore, this study proposes a distributed heterogeneous multi-task and mul…

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…

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…

Resource Allocation in Cooperative Mid-band/THz Networks in the Presence of Mobility
Mohammad Amin Saeidi, Hina Tabassum
https://arxiv.org/abs/2509.23065 https://

Resource Allocation in Cooperative Mid-band/THz Networks in the Presence of Mobility
This paper develops a comprehensive framework to investigate and optimize the downlink performance of cooperative multi-band networks (MBNs) operating on upper mid-band (UMB) and terahertz (THz) frequencies, where base stations (BSs) in each band cooperatively serve users. The framework captures sophisticated features such as near-field channel modeling, fully and partially connected antenna architectures, and users' mobility. First, we consider joint user association and hybrid beamforming opt…

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…

Are you interested in Worker Cooperative game dev studios?
What about building your own someday with fellow collaborators?
Then pop along to this online panel discussion from game devs in cooperatives doing just that! Details below 👇
https://social.coop/@denmanrooke/114955247…

Evolutionary dynamics under coordinated reciprocity
Feipeng Zhang, Bingxin Lin, Lei Zhou, Long Wang
https://arxiv.org/abs/2509.03524 https://arxiv.org/pdf/…

Evolutionary dynamics under coordinated reciprocity
Using past behaviors to guide future actions is essential for fostering cooperation in repeated social dilemmas. Traditional memory-based strategies that focus on recent interactions have yielded valuable insights into the evolution of cooperative behavior. However, as memory length increases, the complexity of analysis grows exponentially, since these strategies need to map every possible action sequence of a given length to subsequent responses. Due to their inherent reliance on exhaustive ma…

DRCP: Diffusion on Reinforced Cooperative Perception for Perceiving Beyond Limits
Lantao Li, Kang Yang, Rui Song, Chen Sun
https://arxiv.org/abs/2509.24903 https://

DRCP: Diffusion on Reinforced Cooperative Perception for Perceiving Beyond Limits
Cooperative perception enabled by Vehicle-to-Everything communication has shown great promise in enhancing situational awareness for autonomous vehicles and other mobile robotic platforms. Despite recent advances in perception backbones and multi-agent fusion, real-world deployments remain challenged by hard detection cases, exemplified by partial detections and noise accumulation which limit downstream detection accuracy. This work presents Diffusion on Reinforced Cooperative Perception (DRCP)…

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…

Cooperative floor staff are about to go on strike as their way of working is changing so that they work on their own and not in pairs as they generally do.
This is a matter of safety at work.
#Employment #Cooperatives

People Are Highly Cooperative with Large Language Models, Especially When Communication Is Possible or Following Human Interaction
Pawe{\l} Niszczota, Tomasz Grzegorczyk, Alexander Pastukhov
https://arxiv.org/abs/2507.18639

People Are Highly Cooperative with Large Language Models, Especially When Communication Is Possible or Following Human Interaction
Machines driven by large language models (LLMs) have the potential to augment humans across various tasks, a development with profound implications for business settings where effective communication, collaboration, and stakeholder trust are paramount. To explore how interacting with an LLM instead of a human might shift cooperative behavior in such settings, we used the Prisoner's Dilemma game -- a surrogate of several real-world managerial and economic scenarios. In Experiment 1 (N=100), part…

Fast Learning of Non-Cooperative Spacecraft 3D Models through Primitive Initialization
Pol Francesch Huc, Emily Bates, Simone D'Amico
https://arxiv.org/abs/2507.19459 https:…

Fast Learning of Non-Cooperative Spacecraft 3D Models through Primitive Initialization
The advent of novel view synthesis techniques such as NeRF and 3D Gaussian Splatting (3DGS) has enabled learning precise 3D models only from posed monocular images. Although these methods are attractive, they hold two major limitations that prevent their use in space applications: they require poses during training, and have high computational cost at training and inference. To address these limitations, this work contributes: (1) a Convolutional Neural Network (CNN) based primitive initializer…

Cooperative Function with Thermal Fluctuations in Mechanical Networks
Ben Pisanty, Jovana Andrejevic, Andrea J. Liu, Sidney R. Nagel
https://arxiv.org/abs/2509.20560 https://

Cooperative Function with Thermal Fluctuations in Mechanical Networks
Elastic networks can be tuned to exhibit complex mechanical responses and have been extensively used to study protein allosteric functionality, where a localized strain regulates the conformation at a distant site. We show that cooperative binding, where two sites each enhance the other's ability to function, can be trained via a symmetric application of the training previously employed for creating network allostery. We identify a crossover temperature above which cooperative functionality bre…

It’s not fair to compare a state-of-the-art-AI-assisted proprietary tool from a trillion-dollar corporation with a hand-coded free and open tool from a small not-for-profit cooperative.
(The latter works.)
https://github.com/orgs/community/discussions/17…

The Github website is extremely slow on Safari · community · Discussion #170758
Select Topic Area Bug Body Over the past few months, Github has been getting slower and slower on Safari. It has now reached a point where it is unusable. Displaying any pull request with more than...

Gemini Is 'Strict and Punitive' While ChatGPT Is 'Catastrophically' Cooperative, Researchers Say https://www.404media.co/gemini-is-strict-and-punitive-while-chatgpt-is-catastrophically-cooperative-researchers-say/…

H-US-Japan: New Book: Cooperative Evangelist: Kagawa Toyohiko and His World, 1888–1960 https://networks.h-net.org/group/announcements/20125743/new-book-cooperative-evangelist-kagawa-toyohiko-and-his-world-1888

Perfect adaptation in eukaryotic gradient sensing using cooperative allosteric binding
Vishnu Srinivasan, Wei Wang, Brian A. Camley
https://arxiv.org/abs/2509.00219 https://

Perfect adaptation in eukaryotic gradient sensing using cooperative allosteric binding
Eukaryotic cells generally sense chemical gradients using the binding of chemical ligands to membrane receptors. In order to perform chemotaxis effectively in different environments, cells need to adapt to different concentrations. We present a model of gradient sensing where the affinity of receptor-ligand binding is increased when a protein binds to the receptor's cytosolic side. This interior protein (allosteric factor) alters the sensitivity of the cell, allowing the cell to adapt to differ…

Multi-population Ensemble Genetic Programming via Cooperative Coevolution and Multi-view Learning for Classification
Mohammad Sadegh Khorshidi, Navid Yazdanjue, Hassan Gharoun, Mohammad Reza Nikoo, Fang Chen, Amir H. Gandomi
https://arxiv.org/abs/2509.19339

Multi-population Ensemble Genetic Programming via Cooperative Coevolution and Multi-view Learning for Classification
This paper introduces Multi-population Ensemble Genetic Programming (MEGP), a computational intelligence framework that integrates cooperative coevolution and the multiview learning paradigm to address classification challenges in high-dimensional and heterogeneous feature spaces. MEGP decomposes the input space into conditionally independent feature subsets, enabling multiple subpopulations to evolve in parallel while interacting through a dynamic ensemble-based fitness mechanism. Each individ…

Crosslisted article(s) found for cs.MA. https://arxiv.org/list/cs.MA/new
[1/1]:
- Cooperative Grasping for Collective Object Transport in Constrained Environments
David Alvear, George Turkiyyah, Shinkyu Park

The evolution of trust as a cognitive shortcut in repeated interactions
Cedric Perret, The Anh Han, Elias Fern\'andez Domingos, Theodor Cimpeanu, Simon T. Powers
https://arxiv.org/abs/2509.04143

The evolution of trust as a cognitive shortcut in repeated interactions
Trust is often thought to increase cooperation. However, game-theoretic models often fail to distinguish between cooperative behaviour and trust. This makes it difficult to measure trust and determine its effect in different social dilemmas. We address this here by formalising trust as a cognitive shortcut in repeated games. This functions by avoiding checking a partner's actions once a threshold level of cooperativeness has been observed. We consider trust-based strategies that implement this …

Crosslisted article(s) found for physics.bio-ph. https://arxiv.org/list/physics.bio-ph/new
[1/1]:
- Perfect adaptation in eukaryotic gradient sensing using cooperative allosteric binding
Vishnu Srinivasan, Wei Wang, Brian A. Camley

Cooperative Jamming Detection Using Low-Rank Structure of Received Signal Matrix
Amir Mehrabian, Georges Kaddoum
https://arxiv.org/abs/2507.20504 https://a…

Cooperative Jamming Detection Using Low-Rank Structure of Received Signal Matrix
Wireless communication can be simply subjected to malicious attacks due to its open nature and shared medium. Detecting jamming attacks is the first and necessary step to adopt the anti-jamming strategies. This paper presents novel cooperative jamming detection methods that use the low-rank structure of the received signal matrix. We employed the likelihood ratio test to propose detectors for various scenarios. We regarded several scenarios with different numbers of friendly and jamming nodes a…

Cooperative SGD with Dynamic Mixing Matrices
Soumya Sarkar, Shweta Jain
https://arxiv.org/abs/2508.14565 https://arxiv.org/pdf/2508.14565

Cooperative SGD with Dynamic Mixing Matrices
One of the most common methods to train machine learning algorithms today is the stochastic gradient descent (SGD). In a distributed setting, SGD-based algorithms have been shown to converge theoretically under specific circumstances. A substantial number of works in the distributed SGD setting assume a fixed topology for the edge devices. These papers also assume that the contribution of nodes to the global model is uniform. However, experiments have shown that such assumptions are suboptimal …

Studio Rúcach @… in collaboration with CREW are excited to announce a two-part masterclass exploring co-operative models for game dev.
Part 1: Navigating Co-Op Mode (Online)
Hear from co-ops creating equitable workplaces in the games industry.

RadioDiff-Loc: Diffusion Model Enhanced Scattering Congnition for NLoS Localization with Sparse Radio Map Estimation
Xiucheng Wang, Qiming Zhang, Nan Cheng
https://arxiv.org/abs/2509.01875

RadioDiff-Loc: Diffusion Model Enhanced Scattering Congnition for NLoS Localization with Sparse Radio Map Estimation
Accurate localization of non-cooperative signal sources in non-line-of-sight (NLoS) environments remains a critical challenge with a wide range of applications, including autonomous navigation, industrial automation, and emergency response. In such settings, traditional positioning techniques relying on line-of-sight (LoS) or cooperative signaling fail due to severe multipath propagation and unknown transmit power. This paper proposes a novel generative inference framework for NLoS localization…

Replaced article(s) found for physics.soc-ph. https://arxiv.org/list/physics.soc-ph/new
[1/1]:
- Q-Learning-Driven Adaptive Rewiring for Cooperative Control in Heterogeneous Networks
Yi-Ning Weng, Hsuan-Wei Lee

Designing the Hybrid Cooperative: A Socio-Technical Architecture for Scalable, Global Coordination Using Blockchain
Henrik Axelsen, Jan Damsgaard
https://arxiv.org/abs/2509.13156

Designing the Hybrid Cooperative: A Socio-Technical Architecture for Scalable, Global Coordination Using Blockchain
Blockchain has been promoted as a remedy for coordination in fragmented, multi-stakeholder ecosystems, yet many projects stall at pilot stage. Using a design-science approach, we develop the Hybrid Cooperative (HC), a digitally native governance architecture that combines smart-contract coordination with a minimal, code-deferent legal interface and jurisdictional modules. This selective decentralization decentralizes rules where programmability lowers agency and verification costs, and centrali…

Machine learning-based multimodal prognostic models integrating pathology images and high-throughput omic data for overall survival prediction in cancer: a systematic review
Charlotte Jennings (National Pathology Imaging Cooperative, Leeds Teaching Hospitals NHS Trust, Leeds, UK), Andrew Broad (National Pathology Imaging Cooperative, Leeds Teaching Hospitals NHS Trust, Leeds, UK), Lucy Godson (National Pathology Imaging Cooperative, Leeds Teaching Hospitals NHS Trust, Leeds, UK), Emily…

Machine learning-based multimodal prognostic models integrating pathology images and high-throughput omic data for overall survival prediction in cancer: a systematic review
Multimodal machine learning integrating histopathology and molecular data shows promise for cancer prognostication. We systematically reviewed studies combining whole slide images (WSIs) and high-throughput omics to predict overall survival. Searches of EMBASE, PubMed, and Cochrane CENTRAL (12/08/2024), plus citation screening, identified eligible studies. Data extraction used CHARMS; bias was assessed with PROBAST+AI; synthesis followed SWiM and PRISMA 2020. Protocol: PROSPERO (CRD42024594745)…

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…

A Cooperative Approach for Knowledge-based Business Process Design in a Public Authority
Mohammad Azarijafari, Luisa Mich, Michele Missikoff, Oleg Missikoff
https://arxiv.org/abs/2507.19842

A Cooperative Approach for Knowledge-based Business Process Design in a Public Authority
Enterprises are currently undergoing profound transformations due to the unpostponable digital transformation. Then, to remain competitive, enterprises must adapt their organisational structures and operations. This organisational shift is also important for small and medium-sized enterprises. A key innovation frontier is the adoption of process-oriented production models. This paper presents a knowledge-based method to support business experts in designing business processes. The method requir…

Cooperative Suppression Strategy for Dual Thermal Transport Channels in Crystalline Materials
Yu Wu, Ying Chen, Shuming Zeng, Hao Zhang, Liujiang Zhou, Chenhan Liu, Su-Huai Wei
https://arxiv.org/abs/2508.17318

Cooperative Suppression Strategy for Dual Thermal Transport Channels in Crystalline Materials
We propose a novel design principle for achieving ultralow thermal conductivity in crystalline materials via a "heavy-light and soft-stiff" structural motif. By combining heavy and light atomic species with soft and stiff bonding networks, both particle-like ($κ_p$) and wave-like ($κ_c$) phonon transport channels are concurrently suppressed. First-principles calculations show that this architecture induces a hierarchical phonon spectrum: soft-bonded heavy atoms generate dense low-frequency mo…

Synesthesia of Machines (SoM)-Based Task-Driven MIMO System for Image Transmission
Sijiang Li, Rongqing Zhang, Xiang Cheng, Jian Tang
https://arxiv.org/abs/2509.02031 https://…

Synesthesia of Machines (SoM)-Based Task-Driven MIMO System for Image Transmission
To support cooperative perception (CP) of networked mobile agents in dynamic scenarios, the efficient and robust transmission of sensory data is a critical challenge. Deep learning-based joint source-channel coding (JSCC) has demonstrated promising results for image transmission under adverse channel conditions, outperforming traditional rule-based codecs. While recent works have explored to combine JSCC with the widely adopted multiple-input multiple-output (MIMO) technology, these approaches …

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…

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

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

CoPAD : Multi-source Trajectory Fusion and Cooperative Trajectory Prediction with Anchor-oriented Decoder in V2X Scenarios
Kangyu Wu, Jiaqi Qiao, Ya Zhang
https://arxiv.org/abs/2509.15984

CoPAD : Multi-source Trajectory Fusion and Cooperative Trajectory Prediction with Anchor-oriented Decoder in V2X Scenarios
Recently, data-driven trajectory prediction methods have achieved remarkable results, significantly advancing the development of autonomous driving. However, the instability of single-vehicle perception introduces certain limitations to trajectory prediction. In this paper, a novel lightweight framework for cooperative trajectory prediction, CoPAD, is proposed. This framework incorporates a fusion module based on the Hungarian algorithm and Kalman filtering, along with the Past Time Attention (…

Robust Real-Time Coordination of CAVs: A Distributed Optimization Framework under Uncertainty
Haojie Bai, Yang Wang, Cong Guo, Xiongwei Zhao, Hai Zhu
https://arxiv.org/abs/2508.21322

Robust Real-Time Coordination of CAVs: A Distributed Optimization Framework under Uncertainty
Achieving both safety guarantees and real-time performance in cooperative vehicle coordination remains a fundamental challenge, particularly in dynamic and uncertain environments. This paper presents a novel coordination framework that resolves this challenge through three key innovations: 1) direct control of vehicles' trajectory distributions during coordination, formulated as a robust cooperative planning problem with adaptive enhanced safety constraints, ensuring a specified level of safety…

CausalMACE: Causality Empowered Multi-Agents in Minecraft Cooperative Tasks
Qi Chai, Zhang Zheng, Junlong Ren, Deheng Ye, Zichuan Lin, Hao Wang
https://arxiv.org/abs/2508.18797 …

CausalMACE: Causality Empowered Multi-Agents in Minecraft Cooperative Tasks
Minecraft, as an open-world virtual interactive environment, has become a prominent platform for research on agent decision-making and execution. Existing works primarily adopt a single Large Language Model (LLM) agent to complete various in-game tasks. However, for complex tasks requiring lengthy sequences of actions, single-agent approaches often face challenges related to inefficiency and limited fault tolerance. Despite these issues, research on multi-agent collaboration remains scarce. In …

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 …

New Book: Cooperative Evangelist: Kagawa Toyohiko and His World, 1888–1960 https://networks.h-net.org/group/announcements/20125742/new-book-cooperative-evangelist-kagawa-toyohiko-and-his-world-1888

Cooperative missile guidance design using Distributed Nonlinear Dynamic Inversion
Sabyasachi Mondal, Bhaskar Biswas, Venkatraman Renganathan
https://arxiv.org/abs/2509.18022 htt…

Cooperative missile guidance design using Distributed Nonlinear Dynamic Inversion
This paper presents a new cooperative guidance algorithm based on Distributed Nonlinear Dynamic Inversion (DNDI) to demonstrate a coordinated missile attack.

Multi-Agent Guided Policy Search for Non-Cooperative Dynamic Games
Jingqi Li, Gechen Qu, Jason J. Choi, Somayeh Sojoudi, Claire Tomlin
https://arxiv.org/abs/2509.24226 https://

Multi-Agent Guided Policy Search for Non-Cooperative Dynamic Games
Multi-agent reinforcement learning (MARL) optimizes strategic interactions in non-cooperative dynamic games, where agents have misaligned objectives. However, data-driven methods such as multi-agent policy gradients (MA-PG) often suffer from instability and limit-cycle behaviors. Prior stabilization techniques typically rely on entropy-based exploration, which slows learning and increases variance. We propose a model-based approach that incorporates approximate priors into the reward function a…

V2V-GoT: Vehicle-to-Vehicle Cooperative Autonomous Driving with Multimodal Large Language Models and Graph-of-Thoughts
Hsu-kuang Chiu, Ryo Hachiuma, Chien-Yi Wang, Yu-Chiang Frank Wang, Min-Hung Chen, Stephen F. Smith
https://arxiv.org/abs/2509.18053

V2V-GoT: Vehicle-to-Vehicle Cooperative Autonomous Driving with Multimodal Large Language Models and Graph-of-Thoughts
Current state-of-the-art autonomous vehicles could face safety-critical situations when their local sensors are occluded by large nearby objects on the road. Vehicle-to-vehicle (V2V) cooperative autonomous driving has been proposed as a means of addressing this problem, and one recently introduced framework for cooperative autonomous driving has further adopted an approach that incorporates a Multimodal Large Language Model (MLLM) to integrate cooperative perception and planning processes. Howe…

AgentMesh: A Cooperative Multi-Agent Generative AI Framework for Software Development Automation
Sourena Khanzadeh
https://arxiv.org/abs/2507.19902 https://

AgentMesh: A Cooperative Multi-Agent Generative AI Framework for Software Development Automation
Software development is a complex, multi-phase process traditionally requiring collaboration among individuals with diverse expertise. We propose AgentMesh, a Python-based framework that uses multiple cooperating LLM-powered agents to automate software development tasks. In AgentMesh, specialized agents - a Planner, Coder, Debugger, and Reviewer - work in concert to transform a high-level requirement into fully realized code. The Planner agent first decomposes user requests into concrete subtas…

Cooperative Design Optimization through Natural Language Interaction
Ryogo Niwa, Shigeo Yoshida, Yuki Koyama, Yoshitaka Ushiku
https://arxiv.org/abs/2508.16077 https://

Cooperative Design Optimization through Natural Language Interaction
Designing successful interactions requires identifying optimal design parameters. To do so, designers often conduct iterative user testing and exploratory trial-and-error. This involves balancing multiple objectives in a high-dimensional space, making the process time-consuming and cognitively demanding. System-led optimization methods, such as those based on Bayesian optimization, can determine for designers which parameters to test next. However, they offer limited opportunities for designers…

A Strongly Polynomial-Time Combinatorial Algorithm for the Nucleolus in Convex Games
Giacoomo Maggiorano, Alessandro Sosso, Gautier Stauffer
https://arxiv.org/abs/2509.02380 htt…

A Strongly Polynomial-Time Combinatorial Algorithm for the Nucleolus in Convex Games
The nucleolus is a fundamental solution concept in cooperative game theory, yet computing it is NP-hard in general. In convex games-where players' marginal contributions grow with coalition size-the only existing polynomial-time algorithm relies on the ellipsoid method. We re-examine a reduced game approach, refuting a previously claimed polynomial-time implementation and clarifying why it fails. By developing new algorithmic ideas and exploiting the structure of least core polyhedra, we show t…

Anyone have any idea if https://Meet.Coop is still being maintained? Maybe someone at @… knows?
It had been working fine, but today, suddenly a few people couldn't get audio to work.…

meet.coop - The Online Meeting Cooperative
Online meeting and conferencing tools, powered by renewable energy running on cooperatively owned and managed infrastructure.

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…

Networked Control and Mean Field Problems Under Diagonal Dominance: Decentralized and Social Optimality
Vivek Khatana, Duo Wang, Petros Voulgaris, Nicola Elia, Naira Hovakimyan
https://arxiv.org/abs/2510.01067

Networked Control and Mean Field Problems Under Diagonal Dominance: Decentralized and Social Optimality
In this article, we employ an input-output approach to expand the study of cooperative multi-agent control and optimization problems characterized by mean-field interactions that admit decentralized and selfish solutions. The setting involves $n$ independent agents that interact solely through a shared cost function, which penalizes deviations of each agent from the group's average collective behavior. Building on our earlier results established for homogeneous agents, we extend the framework t…

Cooperative Sensing Enhanced UAV Path-Following and Obstacle Avoidance with Variable Formation
Changheng Wang, Zhiqing Wei, Wangjun Jiang, Haoyue Jiang, Zhiyong Feng
https://arxiv.org/abs/2508.21316

Cooperative Sensing Enhanced UAV Path-Following and Obstacle Avoidance with Variable Formation
The high mobility of unmanned aerial vehicles (UAVs) enables them to be used in various civilian fields, such as rescue and cargo transport. Path-following is a crucial way to perform these tasks while sensing and collision avoidance are essential for safe flight. In this paper, we investigate how to efficiently and accurately achieve path-following, obstacle sensing and avoidance subtasks, as well as their conflict-free fusion scheduling. Firstly, a high precision deep reinforcement learning (…

Cultural tightness and social cohesion under evolving norms
Filippo Zimmaro, Jacopo Grilli, Mirta Galesic, Alexander J. Stewart
https://arxiv.org/abs/2509.01848 https://

Cultural tightness and social cohesion under evolving norms
Successful collective action on issues from climate change to the maintenance of democracy depends on societal properties such as cultural tightness and social cohesion. How these properties evolve is not well understood because they emerge from a complex interplay between beliefs and behaviors that are usually modeled separately. Here we address this challenge by developing a game-theoretical framework incorporating norm-utility models to study the coevolutionary dynamics of cooperative action…

Large-scale cooperative sulfur vacancy dynamics in two-dimensional MoS2 from machine learning interatomic potentials
Aaron Fl\"ototto, Benjamin Spetzler, Rose von Stackelberg, Martin Ziegler, Erich Runge, Christian Dre{\ss}ler
https://arxiv.org/abs/2508.13790

Large-scale cooperative sulfur vacancy dynamics in two-dimensional MoS2 from machine learning interatomic potentials
The formation of extended sulfur vacancies in MoS2 monolayers is closely associated with catalytic activity and may also be the basis for its memristive behavior. Nanosecond-scale molecular dynamics simulations using machine learning interatomic potentials (MLIPs) reveal key mechanisms of cooperative vacancy transport, including incorporation of vacancies into clusters of arbitrary size. The simulations provide a coherent atomistic explanation for irradiation-induced vacancy patterns observed e…

Touching the tumor boundary: A pilot study on ultrasound based virtual fixtures for breast-conserving surgery
Laura Connolly, Tamas Ungi, Adnan Munawar, Anton Deguet, Chris Yeung, Russell H. Taylor, Parvin Mousavi, Gabor Fichtinger Keyvan Hashtrudi-Zaad
https://arxiv.org/abs/2510.01452

Touching the tumor boundary: A pilot study on ultrasound based virtual fixtures for breast-conserving surgery
Purpose: Delineating tumor boundaries during breast-conserving surgery is challenging as tumors are often highly mobile, non-palpable, and have irregularly shaped borders. To address these challenges, we introduce a cooperative robotic guidance system that applies haptic feedback for tumor localization. In this pilot study, we aim to assess if and how this system can be successfully integrated into breast cancer care. Methods: A small haptic robot is retrofitted with an electrocautery blade t…

Multi-group Bayesian Games
Hongxing Yuan, Xuan Zhang, Chunyu Wei, Yushun Fan
https://arxiv.org/abs/2510.02078 https://arxiv.org/pdf/2510.02078

Multi-group Bayesian Games
This paper presents a model of multi-group Bayesian games (MBGs) to describe the group behavior in Bayesian games, and gives methods to find (strongly) multi-group Bayesian Nash equilibria (MBNE) of this model with a proposed transformation. MBNE represent the optimal strategy \textit{profiles} under the situation where players within a group play a cooperative game, while strongly MBNE characterize the optimal strategy \textit{profiles} under the situation where players within a group play a n…

Cooperative Face Liveness Detection from Optical Flow
Artem Sokolov, Mikhail Nikitin, Anton Konushin
https://arxiv.org/abs/2508.10786 https://arxiv.org/pdf…

Cooperative Face Liveness Detection from Optical Flow
In this work, we proposed a novel cooperative video-based face liveness detection method based on a new user interaction scenario where participants are instructed to slowly move their frontal-oriented face closer to the camera. This controlled approaching face protocol, combined with optical flow analysis, represents the core innovation of our approach. By designing a system where users follow this specific movement pattern, we enable robust extraction of facial volume information through neur…

Enhancing Resilience Against Jamming Attacks: A Cooperative Anti-Jamming Method Using Direction Estimation
Amir Mehrabian, Georges Kaddoum
https://arxiv.org/abs/2507.14775

Enhancing Resilience Against Jamming Attacks: A Cooperative Anti-Jamming Method Using Direction Estimation
The inherent vulnerability of wireless communication necessitates strategies to enhance its security, particularly in the face of jamming attacks. This paper uses the collaborations of multiple sensing nodes (SNs) in the wireless network to present a cooperative anti-jamming approach (CAJ) designed to neutralize the impact of jamming attacks. We propose an eigenvector (EV) method to estimate the direction of the channel vector from pilot symbols. Through our analysis, we demonstrate that with a…

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 Dynamics of Censorship, Misinformation, and Influence Operations: Insights from the Global South and U.S
Zaid Hakami, Yuzhou Feng, Bogdan Carbunar
https://arxiv.org/abs/2509.17933

Cooperative Dynamics of Censorship, Misinformation, and Influence Operations: Insights from the Global South and U.S
Censorship and the distribution of false information, tools used to manipulate what users see and believe, are seemingly at opposite ends of the information access spectrum. Most previous work has examined them in isolation and within individual countries, leaving gaps in our understanding of how these information manipulation tools interact and reinforce each other across diverse societies. In this paper, we study perceptions about the interplay between censorship, false information, and influ…

Cooperative UAV-mounted RISs-assisted Energy-efficient Communications
Hongyang Pan, Yanheng Liu, Geng Sun, Qingqing Wu, Tierui Gong, Pengfei Wang, Dusit Niyato, Chau Yuen
https://arxiv.org/abs/2509.11533

Cooperative UAV-mounted RISs-assisted Energy-efficient Communications
Cooperative reconfigurable intelligent surfaces (RISs) are promising technologies for 6G networks to support a great number of users. Compared with the fixed RISs, the properly deployed RISs may improve the communication performance with less communication energy consumption, thereby improving the energy efficiency. In this paper, we consider a cooperative unmanned aerial vehicle-mounted RISs (UAV-RISs)-assisted cellular network, where multiple RISs are carried and enhanced by UAVs to serve mul…

New Book: Cooperative Evangelist: Kagawa Toyohiko and His World, 1888–1960
https://ift.tt/rMgxb2H
Summer 2026 Vietnamese Language Study with Indiana University Kathleen Evans 09/19/2025 - 9:31am …
via Input 4 RELCFP

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition
Ruiyang Hao, Haibao Yu, Jiaru Zhong, Chuanye Wang, Jiahao Wang, Yiming Kan, Wenxian Yang, Siqi Fan, Huilin Yin, Jianing Qiu, Yao Mu, Jiankai Sun, Li Chen, Walter Zimmer, Dandan Zhang, Shanghang Zhang, Mac Schwager, Wei Huang, Xiaobo Zhang, Ping Luo, Zaiqing Nie
htt…

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition
With the rapid advancement of autonomous driving technology, vehicle-to-everything (V2X) communication has emerged as a key enabler for extending perception range and enhancing driving safety by providing visibility beyond the line of sight. However, integrating multi-source sensor data from both ego-vehicles and infrastructure under real-world constraints, such as limited communication bandwidth and dynamic environments, presents significant technical challenges. To facilitate research in this…

Beyond Line-of-Sight: Cooperative Localization Using Vision and V2X Communication
Annika Wong, Zhiqi Tang, Frank J. Jiang, Karl H. Johansson, Jonas M{\aa}rtensson
https://arxiv.org/abs/2507.20772

Beyond Line-of-Sight: Cooperative Localization Using Vision and V2X Communication
Accurate and robust localization is critical for the safe operation of Connected and Automated Vehicles (CAVs), especially in complex urban environments where Global Navigation Satellite System (GNSS) signals are unreliable. This paper presents a novel vision-based cooperative localization algorithm that leverages onboard cameras and Vehicle-to-Everything (V2X) communication to enable CAVs to estimate their poses, even in occlusion-heavy scenarios such as busy intersections. In particular, we p…

Worker Cooperatives in Game Dev webinar this Wednesday!!!
I'll be moderating a panel with our fantastic speakers from KO_OP, Baby Ghosts, Necrosoft Games, CoLab Collective, and Wild Blue Studios.

Strategic Communication and Language Bias in Multi-Agent LLM Coordination
Alessio Buscemi, Daniele Proverbio, Alessandro Di Stefano, The Anh Han, German Castignani, Pietro Li\`o
https://arxiv.org/abs/2508.00032

Strategic Communication and Language Bias in Multi-Agent LLM Coordination
Large Language Model (LLM)-based agents are increasingly deployed in multi-agent scenarios where coordination is crucial but not always assured. Previous studies indicate that the language used to frame strategic scenarios can influence cooperative behavior. This paper explores whether allowing agents to communicate amplifies these language-driven effects. Leveraging the FAIRGAME framework, we simulate one-shot and repeated games across different languages and models, both with and without comm…

Multi-Satellite Cooperative MIMO Transmission: Statistical CSI-Aware RSMA Precoding Design
Sangwon Jo, Seok-Hwan Park
https://arxiv.org/abs/2508.11132 https://

Multi-Satellite Cooperative MIMO Transmission: Statistical CSI-Aware RSMA Precoding Design
We investigate inter-satellite cooperative transmission in a multiple low-Earth orbit (LEO) satellite communication system to enhance spectral efficiency. Specifically, we design multiple-input multipleoutput (MIMO) precoding at LEO satellites for cooperative rate-splitting multiple access (RSMA). Given the difficulty of acquiring instantaneous channel state information (iCSI) due to long delays and Doppler effects, we formulate an ergodic max-min fairness rate (MMFR) maximization problem based…

Joint Cooperative and Non-Cooperative Localization in WSNs with Distributed Scaled Proximal ADMM Algorithms
Qiaojia Zhu, Xiaojing Shen, Haiqi Liu, Pramod K. Varshney
https://arxiv.org/abs/2509.18213

New Book: Cooperative Evangelist: Kagawa Toyohiko and His World, 1888–1960
https://ift.tt/imVn8PZ
Summer 2026 Vietnamese Language Study with Indiana University Kathleen Evans 09/19/2025 - 9:31am …
via Input 4 RELCFP

Enhancing Multi-Agent Collaboration with Attention-Based Actor-Critic Policies
Hugo Garrido-Lestache, Jeremy Kedziora
https://arxiv.org/abs/2507.22782 https://

Enhancing Multi-Agent Collaboration with Attention-Based Actor-Critic Policies
This paper introduces Team-Attention-Actor-Critic (TAAC), a reinforcement learning algorithm designed to enhance multi-agent collaboration in cooperative environments. TAAC employs a Centralized Training/Centralized Execution scheme incorporating multi-headed attention mechanisms in both the actor and critic. This design facilitates dynamic, inter-agent communication, allowing agents to explicitly query teammates, thereby efficiently managing the exponential growth of joint-action spaces while …

Robustness Enhancement for Multi-Quadrotor Centralized Transportation System via Online Tuning and Learning
Tianhua Gao, Kohji Tomita, Akiya Kamimura
https://arxiv.org/abs/2509.01952

Robustness Enhancement for Multi-Quadrotor Centralized Transportation System via Online Tuning and Learning
This paper introduces an adaptive-neuro geometric control for a centralized multi-quadrotor cooperative transportation system, which enhances both adaptivity and disturbance rejection. Our strategy is to coactively tune the model parameters and learn the external disturbances in real-time. To realize this, we augmented the existing geometric control with multiple neural networks and adaptive laws, where the estimated model parameters and the weights of the neural networks are simultaneously tun…

SlimComm: Doppler-Guided Sparse Queries for Bandwidth-Efficient Cooperative 3-D Perception
Melih Yazgan, Qiyuan Wu, Iramm Hamdard, Shiqi Li, J. Marius Zoellner
https://arxiv.org/abs/2508.13007

SlimComm: Doppler-Guided Sparse Queries for Bandwidth-Efficient Cooperative 3-D Perception
Collaborative perception allows connected autonomous vehicles (CAVs) to overcome occlusion and limited sensor range by sharing intermediate features. Yet transmitting dense Bird's-Eye-View (BEV) feature maps can overwhelm the bandwidth available for inter-vehicle communication. We present SlimComm, a communication-efficient framework that integrates 4D radar Doppler with a query-driven sparse scheme. SlimComm builds a motion-centric dynamic map to distinguish moving from static objects and gene…

Empathy in Explanation
Katherine M. Collins, Kartik Chandra, Adrian Weller, Jonathan Ragan-Kelley, Joshua B. Tenenbaum
https://arxiv.org/abs/2507.21081 https://

Empathy in Explanation
Why do we give the explanations we do? Recent work has suggested that we should think of explanation as a kind of cooperative social interaction, between a why-question-asker and an explainer. Here, we apply this perspective to consider the role that emotion plays in this social interaction. We develop a computational framework for modeling explainers who consider the emotional impact an explanation might have on a listener. We test our framework by using it to model human intuitions about how …

Cooperative Base Station Assignment and Resource Allocation for 6G ISAC Network
Jiajia Liao, Luping Xiang, Shida Zhong, Lixia Xiao, Haochen Liu, Kun Yang
https://arxiv.org/abs/2509.10240

Cooperative Base Station Assignment and Resource Allocation for 6G ISAC Network
In the upcoming 6G networks, integrated sensing and communications (ISAC) will be able to provide a performance boost in both perception and wireless connectivity. This paper considers a multiple base station (BS) architecture to support the comprehensive services of data transmission and multi-target sensing. In this context, a cooperative BS assignment and resource allocation (CBARA) strategy is proposed in this paper, aiming at jointly optimizing the communication and sensing (C&S) performan…

HYCO: Hybrid-Cooperative Learning for Data-Driven PDE Modeling
Lorenzo Liverani, Matthys Steynberg, Enrique Zuazua
https://arxiv.org/abs/2509.14123 https://

HYCO: Hybrid-Cooperative Learning for Data-Driven PDE Modeling
We present Hybrid-Cooperative Learning (HYCO), a hybrid modeling framework that iteratively integrates physics-based and data-driven models through a mutual regularization mechanism. Unlike traditional approaches that impose physical constraints directly on synthetic models, HYCO treats the physical and synthetic components as co-trained agents: the physical and synthetic models are nudged toward agreement, while the synthetic model is enhanced to better fit the available data. This cooperative…

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents
Junjie Qi, Siqi Mao, Tianyi Tan
https://arxiv.org/abs/2508.14131

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents
We propose an improved algorithm by identifying and encouraging cooperative behavior in multi-agent environments. First, we analyze the shortcomings of existing algorithms in addressing multi-agent reinforcement learning problems. Then, based on the existing algorithm MADDPG, we introduce a new parameter to increase the reward that an agent can obtain when cooperative behavior among agents is identified. Finally, we compare our improved algorithm with MADDPG in environments from PettingZoo. The…

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…

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…

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

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

Multiple Active STAR-RIS-Assisted Secure Integrated Sensing and Communication via Cooperative Beamforming
Hyeonho Noh, Hyeonsu Lyu, Hyun Jong Yang
https://arxiv.org/abs/2507.18035

Multiple Active STAR-RIS-Assisted Secure Integrated Sensing and Communication via Cooperative Beamforming
This paper explores an integrated sensing and communication (ISAC) network empowered by multiple active simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs). A base station (BS) furnishes downlink communication to multiple users while concurrently interrogating a sensing target. We jointly optimize the BS transmit beamformer and the reflection/transmission coefficients of every active STAR-RIS in order to maximize the aggregate communication sum-rate, subje…

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…

Flip Co-op: Cooperative Takeovers in Shared Autonomy
Sandeep Banik, Naira Hovakimyan
https://arxiv.org/abs/2509.09281 https://arxiv.org/pdf/2509.09281

Flip Co-op: Cooperative Takeovers in Shared Autonomy
Shared autonomy requires principled mechanisms for allocating and transferring control between a human and an autonomous agent. Existing approaches often rely on blending control inputs between human and autonomous agent or switching rules, which lack theoretical guarantees. This paper develops a game-theoretic framework for modeling cooperative takeover in shared autonomy. We formulate the switching interaction as a dynamic game in which authority is embedded directly into the system dynamics,…

New Book: Cooperative Evangelist: Kagawa Toyohiko and His World, 1888–1960
https://ift.tt/Uj9BXzi
TOC The Asia Pacific Journal of Anthropology, vol 18, 5 (2017) …
via Input 4 RELCFP https://…

MASH: Cooperative-Heterogeneous Multi-Agent Reinforcement Learning for Single Humanoid Robot Locomotion
Qi Liu, Xiaopeng Zhang, Mingshan Tan, Shuaikang Ma, Jinliang Ding, Yanjie Li
https://arxiv.org/abs/2508.10423

MASH: Cooperative-Heterogeneous Multi-Agent Reinforcement Learning for Single Humanoid Robot Locomotion
This paper proposes a novel method to enhance locomotion for a single humanoid robot through cooperative-heterogeneous multi-agent deep reinforcement learning (MARL). While most existing methods typically employ single-agent reinforcement learning algorithms for a single humanoid robot or MARL algorithms for multi-robot system tasks, we propose a distinct paradigm: applying cooperative-heterogeneous MARL to optimize locomotion for a single humanoid robot. The proposed method, multi-agent reinfo…

Safety-Critical Multi-Agent MCTS for Mixed Traffic Coordination at Unsignalized Roundabout
Zhihao Lin, Shuo Liu, Zhen Tian, Dezong Zhao, Jianglin Lan
https://arxiv.org/abs/2509.01856

Safety-Critical Multi-Agent MCTS for Mixed Traffic Coordination at Unsignalized Roundabout
Decision-making at unsignalized roundabouts poses substantial challenges for autonomous vehicles (AVs), particularly in mixed traffic environments where AVs must coordinate safely with human-driven vehicles (HDVs). This paper presents a safety-critical multi-agent Monte Carlo Tree Search (MCTS) framework that integrates both deterministic and probabilistic prediction models to facilitate cooperative decision-making in complex roundabout scenarios. The proposed framework introduces three key inn…

Data Fusion for BS-UE Cooperative MIMO-OFDM ISAC
Yixin Ding, Haoyu Jiang, Xiaoli Xu, Yanan Liang, Yong Zeng
https://arxiv.org/abs/2509.12646 https://arxiv.…

Data Fusion for BS-UE Cooperative MIMO-OFDM ISAC
Integrated sensing and communication (ISAC) is a promising technique for expanding the functionalities of wireless networks with enhanced spectral efficiency. The 3rd Generation Partnership Project (3GPP) has defined six basic sensing operation modes in wireless networks. To further enhance the sensing capability of wireless networks, this paper proposes a new sensing operation mode, i.e., the base station (BS) and user equipment (UE) cooperative sensing. Specifically, after decoding the commun…

Super-additive Cooperation in Language Model Agents
Filippo Tonini, Lukas Galke
https://arxiv.org/abs/2508.15510 https://arxiv.org/pdf/2508.15510

Super-additive Cooperation in Language Model Agents
With the prospect of autonomous artificial intelligence (AI) agents, studying their tendency for cooperative behavior becomes an increasingly relevant topic. This study is inspired by the super-additive cooperation theory, where the combined effects of repeated interactions and inter-group rivalry have been argued to be the cause for cooperative tendencies found in humans. We devised a virtual tournament where language model agents, grouped into teams, face each other in a Prisoner's Dilemma ga…

CAMAR: Continuous Actions Multi-Agent Routing
Artem Pshenitsyn, Aleksandr Panov, Alexey Skrynnik
https://arxiv.org/abs/2508.12845 https://arxiv.org/pdf/250…

CAMAR: Continuous Actions Multi-Agent Routing
Multi-agent reinforcement learning (MARL) is a powerful paradigm for solving cooperative and competitive decision-making problems. While many MARL benchmarks have been proposed, few combine continuous state and action spaces with challenging coordination and planning tasks. We introduce CAMAR, a new MARL benchmark designed explicitly for multi-agent pathfinding in environments with continuous actions. CAMAR supports cooperative and competitive interactions between agents and runs efficiently at…

Task Allocation for Autonomous Machines using Computational Intelligence and Deep Reinforcement Learning
Thanh Thi Nguyen, Quoc Viet Hung Nguyen, Jonathan Kua, Imran Razzak, Dung Nguyen, Saeid Nahavandi
https://arxiv.org/abs/2508.20688

Task Allocation for Autonomous Machines using Computational Intelligence and Deep Reinforcement Learning
Enabling multiple autonomous machines to perform reliably requires the development of efficient cooperative control algorithms. This paper presents a survey of algorithms that have been developed for controlling and coordinating autonomous machines in complex environments. We especially focus on task allocation methods using computational intelligence (CI) and deep reinforcement learning (RL). The advantages and disadvantages of the surveyed methods are analysed thoroughly. We also propose and …

Nonlinear Cooperative Salvo Guidance with Seeker-Limited Interceptors
Lohitvel Gopikannan, Shashi Ranjan Kumar, Abhinav Sinha
https://arxiv.org/abs/2509.15136 https://

Nonlinear Cooperative Salvo Guidance with Seeker-Limited Interceptors
This paper presents a cooperative guidance strategy for the simultaneous interception of a constant-velocity, non-maneuvering target, addressing the realistic scenario where only a subset of interceptors are equipped with onboard seekers. To overcome the resulting heterogeneity in target observability, a fixed-time distributed observer is employed, enabling seeker-less interceptors to estimate the target state using information from seeker-equipped agents and local neighbors over a directed com…

Risk Map As Middleware: Towards Interpretable Cooperative End-to-end Autonomous Driving for Risk-Aware Planning
Mingyue Lei, Zewei Zhou, Hongchen Li, Jiaqi Ma, Jia Hu
https://arxiv.org/abs/2508.07686

Risk Map As Middleware: Towards Interpretable Cooperative End-to-end Autonomous Driving for Risk-Aware Planning
End-to-end paradigm has emerged as a promising approach to autonomous driving. However, existing single-agent end-to-end pipelines are often constrained by occlusion and limited perception range, resulting in hazardous driving. Furthermore, their black-box nature prevents the interpretability of the driving behavior, leading to an untrustworthiness system. To address these limitations, we introduce Risk Map as Middleware (RiskMM) and propose an interpretable cooperative end-to-end driving frame…

Digital Twin-based Cooperative Autonomous Driving in Smart Intersections: A Multi-Agent Reinforcement Learning Approach
Taoyuan Yu, Kui Wang, Zongdian Li, Tao Yu, Kei Sakaguchi, Walid Saad
https://arxiv.org/abs/2509.15099

Digital Twin-based Cooperative Autonomous Driving in Smart Intersections: A Multi-Agent Reinforcement Learning Approach
Unsignalized intersections pose safety and efficiency challenges due to complex traffic flows and blind spots. In this paper, a digital twin (DT)-based cooperative driving system with roadside unit (RSU)-centric architecture is proposed for enhancing safety and efficiency at unsignalized intersections. The system leverages comprehensive bird-eye-view (BEV) perception to eliminate blind spots and employs a hybrid reinforcement learning (RL) framework combining offline pre-training with online fi…

Experimentally-Driven Analysis of Stability in Connected Vehicle Platooning: Insights and Control Strategies
Niladri Dutta, Elham Abolfazli, Themistoklis Charalambous
https://arxiv.org/abs/2507.23078

Experimentally-Driven Analysis of Stability in Connected Vehicle Platooning: Insights and Control Strategies
This paper presents the development of a tangible platform for demonstrating the practical implementation of cooperative adaptive cruise control (CACC) systems, an enhancement to the standard adaptive cruise control (ACC) concept by means of Vehicle-to-Everything (V2X) communication. It involves a detailed examination of existing longitudinal controllers and their performance in homogeneous vehicle platoons. Moreover, extensive tests are conducted using multiple autonomous experimental vehicle …