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Design of Experiments for Reinforcement Learning

169,38 
169,38 
2025-07-31 169.3800 InStock
Nemokamas pristatymas į paštomatus per 18-22 darbo dienų užsakymams nuo 19,00 

Knygos aprašymas

This thesis takes an empirical approach to understanding of the behavior and interactions between the two main components of reinforcement learning: the learning algorithm and the functional representation of learned knowledge. The author approaches these entities using design of experiments not commonly employed to study machine learning methods. The results outlined in this work provide insight as to what enables and what has an effect on successful reinforcement learning implementations so that this learning method can be applied to more challenging problems.

Informacija

Autorius: Christopher Gatti
Serija: Springer Theses
Leidėjas: Springer Nature Switzerland
Išleidimo metai: 2014
Knygos puslapių skaičius: 208
ISBN-10: 3319121960
ISBN-13: 9783319121963
Formatas: Knyga kietu viršeliu
Kalba: Anglų
Žanras: Computer architecture and logic design

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