Design of Experiments for Reinforcement Learning

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 com...

Täydet tiedot

Tallennettuna:
Bibliografiset tiedot
Päätekijä: Gatti, Christopher
Aineistotyyppi: Kirja
Kieli:English
Julkaistu: Springer 2015
Aiheet:
Linkit:https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/57797
Tagit: Lisää tagi
Ei tageja, Lisää ensimmäinen tagi!
Thư viện lưu trữ: Thư viện Trường Đại học Đà Lạt
Kuvaus
Yhteenveto: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.