Elsevier

Artificial Intelligence

Volume 142, Issue 2, December 2002, Pages 121-145
Artificial Intelligence

Plan coordination by revision in collective agent based systems

https://doi.org/10.1016/S0004-3702(02)00273-4Get rights and content
Under an Elsevier user license
open archive

Abstract

In order to model plan coordination behavior of agents we develop a simple framework for representing plans, resources and goals of agents. Plans are represented as directed acyclic graphs of skills and resources that, given adequate initial resources, can realize special resources, called goals. Given the storage costs of resources, application costs of skills, and values of goals, it is possible to reason about the profits of a plan for an agent. We then model two forms of plan coordination behavior between two agents, viz. fusion, aiming at the maximization of the total yield of the agents involved, and collaboration, which aims at the maximization of the individual yield of each agent. We argue how both forms of cooperation can be seen as iterative plan revision processes. We also present efficient polynomial algorithms for agent plan fusion and collaboration that are based on this idea of iterative plan revision. Both the framework and the fusion algorithm will be illustrated by an example from the field of transportation, where agents are transportation companies.

Keywords

Plan representation
Teamwork and cooperation
Multi-agent planning
Distributed resource allocation

Cited by (0)

This paper is an extended version of [23].

1

Supported by the Freight Transport Automation and Multimodality (FTAM) research program.

2

Supported by the Seamless Multimodal Mobility (SMM) research program. Both programs are carried out within the TRAIL research school for Transport, Infrastructure and Logistics.