A generalized learning algorithm for an automaton operating in a multiteacher environment

Ansari, A; Papavassilopoulos, G

dc.contributor.author	Ansari, A	en
dc.contributor.author	Papavassilopoulos, G	en
dc.date.accessioned	2014-03-01T01:47:46Z
dc.date.available	2014-03-01T01:47:46Z
dc.date.issued	1999	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/25316
dc.subject	Indexing Terms	en
dc.subject	Learning Algorithm	en
dc.subject	mimo system	en
dc.subject	Objective Function	en
dc.subject	Multi Input Multi Output	en
dc.subject	Multi Objective Optimization Problem	en
dc.title	A generalized learning algorithm for an automaton operating in a multiteacher environment	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/3477.790442	en
heal.identifier.secondary	http://dx.doi.org/10.1109/3477.790442	en
heal.publicationDate	1999	en
heal.abstract	Learning algorithms for an automaton operating in a multiteacher environment are considered. These algorithms are classified based on the number of actions given as inputs to the environments and the number of responses (outputs) obtained from the environments. In this paper, we present a general class of learning algorithm for multi-input multi-output (MIMO) models. We show that the proposed learning	en
heal.journalName	IEEE Transactions on Systems, Man, and Cybernetics	en
dc.identifier.doi	10.1109/3477.790442	en