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What is Decision Making in Uncertainty & RL about?
This document provides an overview of decision making under uncertainty and reinforcement learning. It covers topics such as subjective probability, utility theory, Bayesian decision problems, sequential sampling, and Markov decision processes. The goal is to describe mathematical frameworks for making optimal decisions when outcomes are uncertain and may depend on the decisions made. Key concepts discussed include subjective probabilities, Bayes
- Author
- ThuanNgDuc
- Language
- EN