Transcription of Reinforcement Learning: A Tutorial Survey and Recent …
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Reinforcement Learning: A Tutorial Survey and Recent …
A. Gosavi Reinforcement learning : A Tutorial Survey and Recent Advances Abhijit Gosavi Department of Engineering Management and Systems Engineering 219 Engineering Management Missouri University of Science and Technology Rolla, MO 65409. Email: Abstract In the last few years, Reinforcement learning (RL), also called adaptive (or approximate) dynamic programming (ADP), has emerged as a powerful tool for solving complex sequential decision-making problems in control theory. Although seminal research in this area was performed in the artificial intelligence (AI) community, more re- cently, it has attracted the attention of optimization theorists because of several noteworthy success stories from operations management. It is on large-scale and complex problems of dynamic optimization, in particular the Markov decision problem (MDP) and its variants, that the power of RL becomes more obvious. It has been known for many years that on large-scale MDPs, the curse of dimensional- ity and the curse of modeling render classical dynamic programming (DP) ineffective.
A. Gosavi Reinforcement Learning: A Tutorial Survey and Recent Advances Abhijit Gosavi Department of Engineering Management and Systems Engineering
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