AI Agents 相关度: 9/10

A Semi-Decentralized Approach to Multiagent Control

Mahdi Al-Husseini, Mykel J. Kochenderfer, Kyle H. Wray
arXiv: 2603.11802v1 发布: 2026-03-12 更新: 2026-03-12

AI 摘要

提出了半去中心化多智能体控制框架SDec-POMDP,并开发了最优策略生成算法RS-SDA*。

主要贡献

  • 提出了SDec-POMDP框架,统一了多种多智能体通信机制
  • 开发了精确求解SDec-POMDP策略的RS-SDA*算法
  • 在多个基准测试和医疗疏散场景验证了算法有效性

方法论

扩展了半马尔可夫通信到POMDP,构建SDec-POMDP模型,并使用A*算法进行策略搜索。

原文摘要

We introduce an expressive framework and algorithms for the semi-decentralized control of cooperative agents in environments with communication uncertainty. Whereas semi-Markov control admits a distribution over time for agent actions, semi-Markov communication, or what we refer to as semi-decentralization, gives a distribution over time for what actions and observations agents can store in their histories. We extend semi-decentralization to the partially observable Markov decision process (POMDP). The resulting SDec-POMDP unifies decentralized and multiagent POMDPs and several existing explicit communication mechanisms. We present recursive small-step semi-decentralized A* (RS-SDA*), an exact algorithm for generating optimal SDec-POMDP policies. RS-SDA* is evaluated on semi-decentralized versions of several standard benchmarks and a maritime medical evacuation scenario. This paper provides a well-defined theoretical foundation for exploring many classes of multiagent communication problems through the lens of semi-decentralization.

标签

multi-agent systems decentralized control POMDP communication

arXiv 分类

cs.AI