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Decision Making Under Uncertainty and Reinforcement Learning|Christos Dimitrakakis

Decision Making Under Uncertainty and Reinforcement Learning : Theory and Algorithms

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Overview

Presents recent research in decision making under uncertainty, and in particular reinforcement learning and learning with expert advice Relate the theory to practical problems in reinforcement learning, artificial intelligence and cognitive science Gives a thorough understanding of statistical decision theory, the meaning of hypothesis testing, automatic methods for designing and interpreting experiments and the relation of statistical decision making to human decision making

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Details

  • ISBN-13: 9783031076121
  • ISBN-10: 3031076125
  • Publisher: Springer
  • Publish Date: December 2022
  • Dimensions: 9.21 x 6.14 x 0.63 inches
  • Shipping Weight: 1.19 pounds
  • Page Count: 243

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