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Knowledge and Information Systems
Erschienen in: Knowledge and Information Systems 1/2014

01.01.2014 | Regular Paper

A flexible coupling approach to multi-agent planning under incomplete information

verfasst von: Alejandro Torreño, Eva Onaindia, Óscar Sapena

Erschienen in: Knowledge and Information Systems | Ausgabe 1/2014

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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. Agents solve MAP tasks through the adoption of an iterative refinement planning procedure that uses single-agent planning technology. In particular, agents will devise refinements through the partial-order planning paradigm, a flexible framework to build refinement plans leaving unsolved details that will be gradually completed by means of new refinements. Our proposal is supported with the implementation of a fully operative MAP system and we show various experiments when running our system over different types of MAP problems, from the most strongly related to the most loosely coupled.
Vorheriger Artikel Context-based information analysis for the Web environment
Nächster Artikel Analyzing the presence of noise in multi-class problems: alleviating its influence with the One-vs-One decomposition

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Fußnoten
1
All the tests were performed on a single machine with a 2.83 GHz Intel Core 2 Quad CPU and 8 GB RAM.
 
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Metadaten
Titel
A flexible coupling approach to multi-agent planning under incomplete information
verfasst von
Alejandro Torreño
Eva Onaindia
Óscar Sapena
Publikationsdatum
01.01.2014
Verlag
Springer London
Erschienen in
Knowledge and Information Systems / Ausgabe 1/2014
Print ISSN: 0219-1377
Elektronische ISSN: 0219-3116
DOI
https://doi.org/10.1007/s10115-012-0569-7

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