Reinforcement Learning and Dynamic Programming Using Function Approximators - Couverture rigide

Livre 17 sur 50: Automation and Control Engineering

Babuska, Robert; Busoniu, Lucian; De Schutter, Bart; Ernst, Damien

 
9781439821084: Reinforcement Learning and Dynamic Programming Using Function Approximators

Synopsis

While Dynamic Programming (DP) has helped solve control problems involving dynamic systems, its value was limited by algorithms that lacked practical scale-up capacity. In recent years, developments in Reinforcement Learning (RL), DP's model-free counterpart, has changed this. Focusing on continuous-variable problems, this unparalleled work provides an introduction to classical RL and DP, followed by a presentation of current methods in RL and DP with approximation. Combining algorithm development with theoretical guarantees, it offers illustrative examples that readers will be able to adapt to their own work.

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À propos de l?auteur

Robert Babuska, Lucian Busoniu, and Bart de Schutter are with the Delft University of Technology. Damien Ernst is with the University of Liege.

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