Explorations of the Practical Issues of Learning Prediction-Control Tasks Using Temporal Difference Learning Methods

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/7050

Full metadata record

DC Field	Value	Language
dc.creator	Isbell, Charles L.	-
dc.date	2004-10-20T20:23:50Z	-
dc.date	2004-10-20T20:23:50Z	-
dc.date	1992-12-01	-
dc.date.accessioned	2013-10-09T02:48:06Z	-
dc.date.available	2013-10-09T02:48:06Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AITR-1424	-
dc.identifier	http://hdl.handle.net/1721.1/7050	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	There has been recent interest in using temporal difference learning methods to attack problems of prediction and control. While these algorithms have been brought to bear on many problems, they remain poorly understood. It is the purpose of this thesis to further explore these algorithms, presenting a framework for viewing them and raising a number of practical issues and exploring those issues in the context of several case studies. This includes applying the TD(lambda) algorithm to: 1) learning to play tic-tac-toe from the outcome of self-play and of play against a perfectly-playing opponent and 2) learning simple one-dimensional segmentation tasks.	-
dc.format	223511 bytes	-
dc.format	456055 bytes	-
dc.format	application/octet-stream	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AITR-1424	-
dc.title	Explorations of the Practical Issues of Learning Prediction-Control Tasks Using Temporal Difference Learning Methods	-
Appears in Collections:	MIT Items

Files in This Item:

There are no files associated with this item.

DSpace JSPUI