Neural networks against genetic algorithms for negotiating agent behaviour prediction

Papaioannou, IV; Roussaki, IG; Anagnostou, ME

dc.contributor.author	Papaioannou, IV	en
dc.contributor.author	Roussaki, IG	en
dc.contributor.author	Anagnostou, ME	en
dc.date.accessioned	2014-03-01T01:28:51Z
dc.date.available	2014-03-01T01:28:51Z
dc.date.issued	2008	en
dc.identifier.issn	15701263	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/18993
dc.subject	Automated negotiations	en
dc.subject	E-marketplace	en
dc.subject	Genetic algorithms	en
dc.subject	Intelligent negotiating agents	en
dc.subject	Neural networks	en
dc.subject.other	Agents	en
dc.subject.other	Algorithms	en
dc.subject.other	Artificial intelligence	en
dc.subject.other	Data structures	en
dc.subject.other	Genetic algorithms	en
dc.subject.other	Internet protocols	en
dc.subject.other	Learning algorithms	en
dc.subject.other	Ambient Intelligence (AmI)	en
dc.subject.other	Automated negotiations	en
dc.subject.other	Contract number	en
dc.subject.other	European Commission (CO)	en
dc.subject.other	Framework Programme (FP)	en
dc.subject.other	Integrated project	en
dc.subject.other	Learning techniques	en
dc.subject.other	Negotiation strategies	en
dc.subject.other	Networked home	en
dc.subject.other	Radial basis function neural network (RBFNN)	en
dc.subject.other	Neural networks	en
dc.title	Neural networks against genetic algorithms for negotiating agent behaviour prediction	en
heal.type	journalArticle	en
heal.identifier.primary	10.3233/WIA-2008-0138	en
heal.identifier.secondary	http://dx.doi.org/10.3233/WIA-2008-0138	en
heal.publicationDate	2008	en
heal.abstract	The design and evaluation of agents handling automated negotiations on behalf of their human or corporate owners is a quite challenging research field. This paper proposes to enhance such agents with learning techniques, in order to achieve more profitable results for the parties they represent. The proposed learning techniques are based on MLP or RBF neural networks (NNs) and are quite lightweight. Alternatively, the agents use Genetic Algorithms (GAs) to predict the behaviour of their opponents. All designed approaches aim to reduce the cases of unsuccessful negotiations and maximize the client's utility. The designed NN- and GA-assisted negotiation strategies This work has in part been supported by the project ""Amigo - Ambient intelligence for the networked home environment"". The Amigo project is funded by the European Commission as an integrated project (IP) in the Sixth Framework Programme under the contract number IST 004182. For more information you may refer to www.amigo-project.org. have been compared and empirically evaluated via numerous experiments. © 2008 - IOS Press and the authors. All right reserved.	en
heal.journalName	Web Intelligence and Agent Systems	en
dc.identifier.doi	10.3233/WIA-2008-0138	en
dc.identifier.volume	6	en
dc.identifier.issue	2	en
dc.identifier.spage	217	en
dc.identifier.epage	233	en