Analysis of adaptability of Reinforcement Learning approach
Multitopic Conference（2011）
摘要
Reinforcement Learning is a powerful tool which is being used for solving many optimization problems including power system scheduling problems. Even though there are theoretical results which suggest that under specified technical conditions, RL algorithms are adaptive, however, for power system scheduling problems the potential of adaptability is not still explored. In this paper, we explore, through simulation studies, the adaptability of an RL algorithm considering a simple multi stage decision making problem.
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关键词
decision making,learning (artificial intelligence),optimisation,power engineering computing,power system economics,power system management,multistage decision making problem,optimization problems,power system scheduling problems,reinforcement learning adaptability analysis,simulation studies,reinforcement learning,adaptive algorithms,multi stage decision making problems,scheduling problem,power system,learning artificial intelligence,optimization problem
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