A Semi-Decentralized Approach to Multiagent Control

2026-03-12

AI Summary

This work addresses cooperative multiagent control under communication uncertainty by proposing a semi-decentralized partially observable Markov decision process (SDec-POMDP) framework. It is the first to model communication actions as a stochastic temporal process and unifies Dec-POMDP and Multiagent POMDP through a probabilistic representation of communication history, thereby enabling flexible explicit communication mechanisms. Building on this formulation, the authors develop the Recursive Small-step Semi-Decentralized A* (RS-SDA*) algorithm to compute exact optimal policies. Empirical evaluation across multiple standard benchmarks and a maritime medical evacuation scenario demonstrates the efficacy of the approach, offering both a theoretical foundation and a practical toolkit for modeling and optimizing communication in multiagent systems.

Technology Category

• Multiagent Systems: Agent Communication
• Planning, Routing, and Scheduling: Planning with Markov Models (MDPs, POMDPs)
• Reasoning under Uncertainty: Sequential Decision Making

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Agentic search
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

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.

Problem

• multiagent control
• communication uncertainty
• semi-decentralization
• POMDP
• cooperative agents

Innovation

• semi-decentralization
• SDec-POMDP
• multiagent control
• communication uncertainty
• RS-SDA*