Publication
Self-managing agents for dynamic scheduling in manufacturing
| dc.contributor.author | Madureira, Ana Maria | |
| dc.contributor.author | Santos, Joaquim | |
| dc.contributor.author | Pereira, Ivo | |
| dc.date.accessioned | 2013-05-09T15:59:38Z | |
| dc.date.available | 2013-05-09T15:59:38Z | |
| dc.date.issued | 2008 | |
| dc.date.updated | 2013-04-23T11:15:21Z | |
| dc.description.abstract | The main purpose of this paper is to propose a Multi-Agent Autonomic and Bio-Inspired based framework with selfmanaging capabilities to solve complex scheduling problems using cooperative negotiation. Scheduling resolution requires the intervention of highly skilled human problem-solvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing (AC) evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. | por |
| dc.identifier | DOI 10.1145/1388969.1389045 | |
| dc.identifier.isbn | 9781605581316 | |
| dc.identifier.uri | http://hdl.handle.net/10400.22/1534 | |
| dc.language.iso | eng | por |
| dc.publisher | ACM Press | por |
| dc.relation.publisherversion | http://dl.acm.org/citation.cfm?doid=1388969.1389045 | |
| dc.subject | Artificial intelligence | por |
| dc.subject | Problem solving, control methods, and search – scheduling | por |
| dc.subject | Distributed artificial intelligence - multiagent systems | por |
| dc.title | Self-managing agents for dynamic scheduling in manufacturing | por |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | Atlanta, GA, USA, 2008 | por |
| oaire.citation.title | Proceedings of the GECCO conference companion on Genetic and evolutionary computation - GECCO '08 | por |
| person.familyName | Madureira | |
| person.familyName | Pereira | |
| person.givenName | Ana Maria | |
| person.givenName | Ivo | |
| person.identifier.ciencia-id | 7F1D-5AF2-A101 | |
| person.identifier.ciencia-id | 3E18-2D4C-0E14 | |
| person.identifier.orcid | 0000-0002-0264-4710 | |
| person.identifier.orcid | 0000-0001-5440-3225 | |
| person.identifier.rid | AAH-1056-2021 | |
| person.identifier.rid | N-1713-2016 | |
| person.identifier.scopus-author-id | 8634629500 | |
| person.identifier.scopus-author-id | 36675461900 | |
| rcaap.rights | openAccess | por |
| rcaap.type | conferenceObject | por |
| relation.isAuthorOfPublication | cd5e5eb7-cf63-48c6-b6b9-a9db2fedebab | |
| relation.isAuthorOfPublication | 097b47eb-e9f1-40cb-9fe3-ca46efc578cb | |
| relation.isAuthorOfPublication.latestForDiscovery | 097b47eb-e9f1-40cb-9fe3-ca46efc578cb |