2022
DOI: 10.1007/978-3-030-85918-3_9
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Configurable Environments in Reinforcement Learning: An Overview

Abstract: Reinforcement Learning (RL) has emerged as an effective approach to address a variety of complex control tasks. In a typical RL problem, an agent interacts with the environment by perceiving observations and performing actions, with the ultimate goal of maximizing the cumulative reward. In the traditional formulation, the environment is assumed to be a fixed entity that cannot be externally controlled. However, there exist several real-world scenarios in which the environment offers the opportunity to configur… Show more

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