Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more /: apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more. (2018)

Record Type:
Book
Title:
Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more /: apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more. (2018)
Main Title:
Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more
Further Information:
Note: Maxim Lapan.
Authors:
Lapan, Maxim
Contents:
Table of ContentsWhat is Reinforcement Learning?OpenAI GymDeep Learning with PyTorchThe Cross-Entropy MethodTabular Learning and the Bellman EquationDeep Q-NetworksDQN ExtensionsStocks Trading Using RLPolicy Gradients – An AlternativeThe Actor-Critic MethodAsynchronous Advantage Actor-CriticChatbots Training with RL Web NavigationContinuous Action SpaceTrust Regions – TRPO, PPO, and ACKTRBlack-Box Optimization in RLBeyond Model-Free – ImaginationAlphaGo Zero.
Publisher Details:
Birmingham : Packt Publishing
Publication Date:
2018
Extent:
1 online resource
Subjects:
006.31
Reinforcement learning
Languages:
English
ISBNs:
9781788839303
Notes:
Note: Description based on CIP data; resource not viewed.
Access Rights:
Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
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Physical Locations:
British Library HMNTS - ELD.DS.310239
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01_237.xml