Latest Articles for Multi-agent Systems

Strategies to enhance agent communication in multi-hop wireless networks.

Study reveals quick paths to efficient Nash equilibria in potential games.

This study explores how agents communicate through imitation of useful signals.

LAGMA improves multi-agent cooperation and learning efficiency through goal guidance.

A novel method for agents to optimize performance while ensuring constraints are met.

A new algorithm enhances computer learning in competitive games.

Exploring quantum computing's role in improving multi-agent learning efficiency.

Agents learn strategic gameplay in Pommerman through a structured training approach.

LawLuo combines multiple agents for enhanced legal consultation experiences.

Examining how agents achieve consensus despite disrupted communication.

New learning algorithms improve agent interactions in shared environments.

This article examines communication and feedback in decision-making scenarios.

Research unveils advanced settings for observing language growth among artificial agents.

An in-depth look at the implications of centralized critics in MARL.

An overview of CTDE methods in multi-agent reinforcement learning.

Exploring vulnerabilities of cooperative multi-agent systems to backdoor attacks.

OpenRC algorithm helps agents agree on averages despite changes in the network.

Examining the impact of data quality on offline multi-agent reinforcement learning research.

Agents can coordinate effectively using localized information.

A look into how agents interact over time in dynamic games.

A new framework enhances decision-making in uncertain multi-agent environments using VAE technology.

Innovative graph designs enhance robot communication and resilience.

An exploration of strategies in differential games and their real-world applications.

MARC enhances agent collaboration in complex environments for better learning outcomes.