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Document Type : Latin Dissertation
Language of Document : English
Record Number : 150252
Doc. No : ET22044
Main Entry : Sungwook Yoon
Title Proper : LEARNING CONTROL KNOWLEDGE FOR AI PLANNING DOMAINS
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : We consider techniques for learning to plan in deterministic and stochastic Arti-ficial Intelligence (AI) planning domains. Many AI planning domains have structurethat can be exploited during planning. However, traditional automated techniquesfail to capture and use such structure and as a result do not scale well as the size ofthe problems grows. Planning systems that exploit human-specified domain struc-ture have shown impressive performance. In this thesis, we explore automated tech-niques that can identify domain-specific structure in AI planning domains. We applymachine-learning algorithms to solved problem instances to find control knowledgedescribing useful stru...,..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 : TL45240.pdf
Title and statement of responsibility and : LEARNING CONTROL KNOWLEDGE FOR AI PLANNING DOMAINS [Thesis]
 
 
 
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