Basic Concepts of Reinforcement Learning

Uwe Lorenz

Chapter 2 in Reinforcement Learning From Scratch, 2022, pp 15-22 from Springer

Abstract: Abstract Reinforcement learning automatically generates goal-oriented agent controls that are as efficient as possible. This chapter describes what a software agent is and how it generates more or less intelligent behavior in an environment with its “policy.” The structure of the basic model of reinforcement learning is described and the concept of intelligence in terms of individual utility maximization is introduced. In addition, some formal means are introduced. It is shown how interdependent states are evaluated with the help of Bellman’s equation and what role the “optimal policy” plays in this process.

Date: 2022
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DOI: 10.1007/978-3-031-09030-1_2

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