Observational Learning
Reinforcement Schedules
Associative Learning
Reinforcement
Purposive Learning
Avoidance Learning and Learned Helplessness
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1Department of Computer Science and Engineering, College of Engineering, The Ohio State University, Columbus, Ohio 43210, United States.
我们开发了RLSynC,这是一种用于化学合成计划的新型强化学习方法. 这种方法增强了反合成中的synthon完成,提高了高达14.9%的准确性.
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