Multi-machine scheduling-a multi-agent learning approach

Wilfried Brauer, Gerhard Weiss

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

38 Scopus citations

Abstract

Multi machine scheduling, that is, the assignment of jobs to machines such that certain performance demands like cost and time effectiveness are fulfilled, is a ubiquitous and complex activity in everyday life. The paper presents an approach to multi machine scheduling that follows the multiagent learning paradigm known from the field of distributed artificial intelligence. According to this approach the machines collectively and as a whole learn and iteratively refine appropriate schedules. The major characteristic of this approach is that learning is distributed over several machines, and that the individual machines carry out their learning activities in a parallel and asynchronous way.

Original languageEnglish
Title of host publicationProceedings - International Conference on Multi Agent Systems, ICMAS 1998
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages42-48
Number of pages7
ISBN (Print)081868500X, 9780818685002
DOIs
StatePublished - 1998
Event1998 International Conference on Multi Agent Systems, ICMAS 1998 - Pans, France
Duration: 3 Jul 19987 Jul 1998

Publication series

NameProceedings - International Conference on Multi Agent Systems, ICMAS 1998

Conference

Conference1998 International Conference on Multi Agent Systems, ICMAS 1998
Country/TerritoryFrance
CityPans
Period3/07/987/07/98

Fingerprint

Dive into the research topics of 'Multi-machine scheduling-a multi-agent learning approach'. Together they form a unique fingerprint.

Cite this