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學(xué)術(shù)動態(tài)

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講座題目:Tutorial on Reinforcement Learning and Its Applications

作者: 編輯: 發(fā)布時間:2019-11-06

講座題目:Tutorial on Reinforcement Learning and Its Applications

主講嘉賓:Prof. Haibing Lu, Department Chair of Information Systems and Analytics, Santa Clara University

講座時間:2019年11月8日 10:00-11:30

講座地點:bwin必贏唯一官網(wǎng)311教室

 

摘要:Reinforcement learning, in the context of artificial intelligence, is a type of dynamic programming that trains algorithms using a system of reward and punishment. A reinforcement learning algorithm, or agent, learns by interacting with its environment. The agent receives rewards by performing correctly and penalties for performing incorrectly. The agent learns without intervention from a human by maximizing its reward and minimizing its penalty. The advantage of this approach to artificial intelligence is that it allows an AI program to learn without a programmer spelling out how an agent should perform the task. Reinforcement learning has found a number of practical applications, including self-driving cars, robots, advertising, gaming, manufacturing, trading, inventory management, pricing, and many others.


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