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Temporal Difference Learning: Reinforcement learning, Monte Carlo method, Dynamic programming, Bootstrap aggregating, Bellman equation - Softcover
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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Temporal difference (TD) learning is a prediction method. It has been mostly used for solving the reinforcement learning problem. "TD learning is a combination of Monte Carlo ideas and dynamic programming (DP) ideas." TD resembles a Monte Carlo method because it learns by sampling the environment according to some policy. TD is related to dynamic programming techniques because it approximates its current estimate based on previously learned estimates (a process known as bootstrapping). The TD learning algorithm is related to the temporal difference model of animal learning.
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Temporal Difference Learning | Reinforcement learning, Monte Carlo method, Dynamic programming, Bootstrap aggregating, Bellman equation
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Taschenbuch. Zustand: Neu. Temporal Difference Learning | Reinforcement learning, Monte Carlo method, Dynamic programming, Bootstrap aggregating, Bellman equation | Klaas Apostol | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786139274529 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 135642610
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