Deep reinforcement learning hands-on :: apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more /
This book is a practical, developer-oriented introduction to deep reinforcement learning (RL). Explore the theoretical concepts of RL, before discovering how deep learning (DL) methods and tools are making it possible to solve more complex and challenging problems than ever before. Apply deep RL met...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham, UK :
Packt Publishing,
2018.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | This book is a practical, developer-oriented introduction to deep reinforcement learning (RL). Explore the theoretical concepts of RL, before discovering how deep learning (DL) methods and tools are making it possible to solve more complex and challenging problems than ever before. Apply deep RL methods to training your agent to beat arcade ... |
| Beschreibung: | "Expert insight." |
| Beschreibung: | 1 online resource (1 volume) : illustrations |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781788839303 1788839307 1788834240 9781788834247 |
Internformat
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| 505 | 0 | |a 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. | |
| 520 | |a This book is a practical, developer-oriented introduction to deep reinforcement learning (RL). Explore the theoretical concepts of RL, before discovering how deep learning (DL) methods and tools are making it possible to solve more complex and challenging problems than ever before. Apply deep RL methods to training your agent to beat arcade ... | ||
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| 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. |
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| spelling | Lapan, Maxim, author. Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more / Maxim Lapan. Birmingham, UK : Packt Publishing, 2018. 1 online resource (1 volume) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier data file Online resource; title from cover (Safari, viewed July 30, 2018). "Expert insight." Includes bibliographical references and index. 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. This book is a practical, developer-oriented introduction to deep reinforcement learning (RL). Explore the theoretical concepts of RL, before discovering how deep learning (DL) methods and tools are making it possible to solve more complex and challenging problems than ever before. Apply deep RL methods to training your agent to beat arcade ... Reinforcement learning. http://id.loc.gov/authorities/subjects/sh92000704 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Natural language processing (Computer science) http://id.loc.gov/authorities/subjects/sh88002425 Artificial intelligence. http://id.loc.gov/authorities/subjects/sh85008180 Natural Language Processing https://id.nlm.nih.gov/mesh/D009323 Artificial Intelligence https://id.nlm.nih.gov/mesh/D001185 Machine Learning https://id.nlm.nih.gov/mesh/D000069550 Apprentissage par renforcement (Intelligence artificielle) Apprentissage automatique. Traitement automatique des langues naturelles. Intelligence artificielle. artificial intelligence. aat COMPUTERS General. bisacsh Artificial intelligence fast Machine learning fast Natural language processing (Computer science) fast Reinforcement learning fast Electronic book. has work: Deep Reinforcement Learning Hands-On (Text) https://id.oclc.org/worldcat/entity/E39PCXfrHBJd8R88mbQmX6bWpd https://id.oclc.org/worldcat/ontology/hasWork Print version: Lapan, Maxim. Deep Reinforcement Learning Hands-On : Apply Modern RL Methods, with Deep Q-Networks, Value Iteration, Policy Gradients, TRPO, AlphaGo Zero and More. Birmingham : Packt Publishing Ltd, ©2018 9781788834247 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1837369 Volltext |
| spellingShingle | Lapan, Maxim Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more / 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. Reinforcement learning. http://id.loc.gov/authorities/subjects/sh92000704 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Natural language processing (Computer science) http://id.loc.gov/authorities/subjects/sh88002425 Artificial intelligence. http://id.loc.gov/authorities/subjects/sh85008180 Natural Language Processing https://id.nlm.nih.gov/mesh/D009323 Artificial Intelligence https://id.nlm.nih.gov/mesh/D001185 Machine Learning https://id.nlm.nih.gov/mesh/D000069550 Apprentissage par renforcement (Intelligence artificielle) Apprentissage automatique. Traitement automatique des langues naturelles. Intelligence artificielle. artificial intelligence. aat COMPUTERS General. bisacsh Artificial intelligence fast Machine learning fast Natural language processing (Computer science) fast Reinforcement learning fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh92000704 http://id.loc.gov/authorities/subjects/sh85079324 http://id.loc.gov/authorities/subjects/sh88002425 http://id.loc.gov/authorities/subjects/sh85008180 https://id.nlm.nih.gov/mesh/D009323 https://id.nlm.nih.gov/mesh/D001185 https://id.nlm.nih.gov/mesh/D000069550 |
| title | Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more / |
| title_auth | Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more / |
| title_exact_search | Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more / |
| title_full | Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more / Maxim Lapan. |
| title_fullStr | Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more / Maxim Lapan. |
| title_full_unstemmed | Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more / Maxim Lapan. |
| title_short | Deep reinforcement learning hands-on : |
| title_sort | deep reinforcement learning hands on apply modern rl methods with deep q networks value iteration policy gradients trpo alphago zero and more |
| title_sub | apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more / |
| topic | Reinforcement learning. http://id.loc.gov/authorities/subjects/sh92000704 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Natural language processing (Computer science) http://id.loc.gov/authorities/subjects/sh88002425 Artificial intelligence. http://id.loc.gov/authorities/subjects/sh85008180 Natural Language Processing https://id.nlm.nih.gov/mesh/D009323 Artificial Intelligence https://id.nlm.nih.gov/mesh/D001185 Machine Learning https://id.nlm.nih.gov/mesh/D000069550 Apprentissage par renforcement (Intelligence artificielle) Apprentissage automatique. Traitement automatique des langues naturelles. Intelligence artificielle. artificial intelligence. aat COMPUTERS General. bisacsh Artificial intelligence fast Machine learning fast Natural language processing (Computer science) fast Reinforcement learning fast |
| topic_facet | Reinforcement learning. Machine learning. Natural language processing (Computer science) Artificial intelligence. Natural Language Processing Artificial Intelligence Machine Learning Apprentissage par renforcement (Intelligence artificielle) Apprentissage automatique. Traitement automatique des langues naturelles. Intelligence artificielle. artificial intelligence. COMPUTERS General. Artificial intelligence Machine learning Reinforcement learning Electronic book. |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1837369 |
| work_keys_str_mv | AT lapanmaxim deepreinforcementlearninghandsonapplymodernrlmethodswithdeepqnetworksvalueiterationpolicygradientstrpoalphagozeroandmore |