Universal sequential decisions in unknown environments

dc.contributor.author	Hutter, Marcus
dc.date.accessioned	2015-09-04T00:05:42Z
dc.date.available	2015-09-04T00:05:42Z
dc.date.issued	2001
dc.description.abstract	We give a brief introduction to the AIXI model, which unifies and overcomes the limitations of sequential decision theory and universal Solomonoff induction. While the former theory is suited for active agents in known environments, the latter is suited for passive prediction of unknown environments.	en_AU
dc.identifier.isbn	90-393-2874-9	en_AU
dc.identifier.issn	1389-5184	en_AU
dc.identifier.uri	http://hdl.handle.net/1885/15169
dc.publisher	Utrecht University	en_AU
dc.relation.ispartof	Proceedings of the fifth European Workshop on Reinforcement Learning (EWRL-5)	en_AU
dc.rights	© The Author(s)	en_AU
dc.subject	Artificial intelligence	en_AU
dc.subject	Rational agents	en_AU
dc.subject	sequential decision theory	en_AU
dc.subject	universal Solomonoff induction	en_AU
dc.subject	algorithmic probability	en_AU
dc.title	Universal sequential decisions in unknown environments	en_AU
dc.type	Conference paper	en_AU
local.bibliographicCitation.lastpage	26	en_AU
local.bibliographicCitation.startpage	25	en_AU
local.contributor.affiliation	Hutter, M., Research School of Computer Science, The Australian National University	en_AU
local.contributor.authoruid	u4350841	en_AU
local.type.status	Published Version	en_AU

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