SCOPUS 정보 검색 플랫폼

IJCAI International Joint Conference on Artificial Intelligence

Volumn 2, Issue , 1999, Pages 1324-1331

A sparse sampling algorithm for near-optimal planning in large Markov decision processes

(3) Kearns, Michael a Mansour, Yishay b Ng, Andrew Y c

a AT AND T LABS RESEARCH (United States)

b TEL AVIV UNIVERSITY (Israel)

c UNIVERSITY OF CALIFORNIA (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DEGREE OF APPROXIMATION; DISCOUNT FACTORS; INFINITE STATE SPACE; MARKOV DECISION PROCESSES; NEAR-OPTIMAL POLICIES; OPTIMAL POLICIES; STOCHASTIC ENVIRONMENT; TRADITIONAL PLANNING;

ARTIFICIAL INTELLIGENCE; FORESTRY; MARKOV PROCESSES; OPTIMIZATION; PLANNING; REINFORCEMENT LEARNING; STOCHASTIC MODELS;

LEARNING ALGORITHMS;

EID: 84880649215 PISSN: 10450823 EISSN: None Source Type: Conference Proceeding
DOI: None Document Type: Conference Paper

Times cited : (138)

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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.