IMITATING AGENT GAME STRATEGIES USING A SCALABLE MARKOV MODEL

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" IMITATING AGENT GAME STRATEGIES USING A SCALABLE MARKOV MODEL "

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	151324
Doc. No	:	ET23116
Main Entry	:	PRIYATH T. SANDANAYAKE
Title Proper	:	IMITATING AGENT GAME STRATEGIES USING A SCALABLE MARKOV MODEL
Note	:	This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract	:	Humans exhibit regularities in almost everything they do. We descn'be a scalableMarkov model derived h m the behavior patterns of an agent, which is used to determinestrategies by predicting which action a user is likely to execute next. The modeling of theuser's behavior is accomplished only by observations without incorporating applicationdetails or the user's goals. We evaluate the predictive accuracy of this approach on alarge dataset collected tiom sample Wumpus World games. We demonstrate h m thisapproach that the model can correctly predict the user's next action with mirdmalcomputation and memory resources. Such predictions can then be used to imitate playerstrategies in a variety of games and other strategic domains, either to assist or to obstructthe user..-....,....-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject	:	Electericl tess
	:	برق
electronic file name	:	TL46350.pdf
Title and statement of responsibility and	:	IMITATING AGENT GAME STRATEGIES USING A SCALABLE MARKOV MODEL [Thesis]