A Flexible Coupling Approach to Multi-Agent Planning under Incomplete Information

TL;DR

This paper presents a versatile multi-agent planning framework that effectively handles complex, strongly-coupled problems under incomplete information by sharing only essential data among agents.

Contribution

It introduces a general-purpose MAP framework capable of managing any coupling level with incomplete information, emphasizing partial awareness and critical information sharing.

Findings

Effective in complex, strongly-coupled scenarios

Handles incomplete information with partial agent awareness

Reduces communication by sharing only critical data

Abstract

Multi-agent planning (MAP) approaches are typically oriented at solving loosely-coupled problems, being ineffective to deal with more complex, strongly-related problems. In most cases, agents work under complete information, building complete knowledge bases. The present article introduces a general-purpose MAP framework designed to tackle problems of any coupling levels under incomplete information. Agents in our MAP model are partially unaware of the information managed by the rest of agents and share only the critical information that affects other agents, thus maintaining a distributed vision of the task.