Active learning of group-structured environments

Bartók, Gábor and Szepesvári, Csaba and Zilles, Sandra (2008) Active learning of group-structured environments. In: ALT 2008. 19th international conference on algorithmic learning theory. Budapest, 2008. (Lecture notes in artificial intelligence 5254.).

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Abstract

The question investigated in this paper is to what extent an input representation influences the success of learning, in particular from the point of view of analyzing agents that can interact with their environment. We investigate learning environments that have a group structure. We introduce a learning model in different variants and study under which circumstances group structures can be learned efficiently from experimenting with group generators (actions). Negative results are presented, even without efficiency constraints, for rather general classes of groups showing that even with group structure, learning an environment from partial information is far from trivial. However, positive results for special subclasses of Abelian groups turn out to be a good starting point for the design of efficient learning algorithms based on structured representations.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Depositing User: Eszter Nagy
Date Deposited: 11 Dec 2012 15:32
Last Modified: 11 Dec 2012 15:32
URI: http://eprints.sztaki.hu/id/eprint/5598

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