Algorithms for Reinforcement Learning

Name: Algorithms for Reinforcement Learning
Brand: Springer International Publishing AG
SKU: 9783031004230
Price: 163.65 RON
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Autor: Szepesvári, Csaba

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Editura: Springer International Publishing AG

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Reinforcement learning is a learning paradigm concerned with learning to control a system so as to m...

Informații despre carte

Autor

Szepesvári, Csaba

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2010

Pagini

EAN

9783031004230

ISBN

303100423X

Enbook ID

39298048

Editura

Springer International Publishing AG

Greutate

214

Dimensiuni

191 x 235 x 7

Descriere completă

Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms' merits and limitations. Reinforcement learning is of great interest because of the large number of practical applications that it can be used to address, ranging from problems in artificial intelligence to operations research or control engineering. In this book, we focus on those algorithms of reinforcement learning that build on the powerful theory of dynamic programming. We give a fairly comprehensive catalog of learning problems, describe the core ideas, note a large number of state of the art algorithms, followed by the discussion of their theoretical properties and limitations.Table of Contents: Markov Decision Processes / Value Prediction Problems / Control / For Further Exploration

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