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Planning with Markov Decision Processes: An AI Perspective (Synthesis Lectures on Artificial Intelligence and Machine Learning)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 35.19
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In English.
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Condition: New. 1st edition NO-PA16APR2015-KAP.
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Planning with Markov Decision Processes : An AI Perspective
Language: English
Published by Springer International Publishing, 2012
ISBN 10: 3031004310 ISBN 13: 9783031004315
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Markov Decision Processes (MDPs) are widely popular in Artificial Intelligence for modeling sequential decision-making scenarios with probabilistic dynamics. They are the framework of choice when designing an intelligent agent that needs to act for long periods of time in an environment where its actions could have uncertain outcomes. MDPs are actively researched in two related subareas of AI, probabilistic planning and reinforcement learning. Probabilistic planning assumes known models for the agent's goals and domain dynamics, and focuses on determining how the agent should behave to achieve its objectives. On the other hand, reinforcement learning additionally learns these models based on the feedback the agent gets from the environment. This book provides a concise introduction to the use of MDPs for solving probabilistic planning problems, with an emphasis on the algorithmic perspective. It covers the whole spectrum of the field, from the basics to state-of-the-art optimal and approximation algorithms. We first describe the theoretical foundations of MDPs and the fundamental solution techniques for them. We then discuss modern optimal algorithms based on heuristic search and the use of structured representations. A major focus of the book is on the numerous approximation schemes for MDPs that have been developed in the AI literature. These include determinization-based approaches, sampling techniques, heuristic functions, dimensionality reduction, and hierarchical representations. Finally, we briefly introduce several extensions of the standard MDP classes that model and solve even more complex planning problems. Table of Contents: Introduction / MDPs / Fundamental Algorithms / Heuristic Search Algorithms / Symbolic Algorithms / Approximation Algorithms / Advanced Notes.
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Planning with Markov Decision Processes: An AI Perspective (Synthesis Lectures on Artificial Intelligence and Machine Learning)
Language: English
Published by Morgan & Claypool Publishers, 2012
ISBN 10: 1608458865 ISBN 13: 9781608458868
Paperback. Condition: Good. Good. Dust Jacket NOT present. CD WILL BE MISSING. . SHIPS FROM MULTIPLE LOCATIONS. book.
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Hardcover. Condition: New. In shrink wrap. Looks like an interesting title!
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Condition: As New. Unread book in perfect condition.
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Personalized Computational Hemodynamics: Models, Methods, and Applications for Vascular Surgery and Antitumor Therapy
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 139.59
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Personalized Computational Hemodynamics : Models, Methods, and Applications for Vascular Surgery and Antitumor Therapy
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
£ 139.58
£ 15 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New.
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Personalized Computational Hemodynamics : Models, Methods, and Applications for Vascular Surgery and Antitumor Therapy
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
£ 153.71
£ 15 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: As New. Unread book in perfect condition.
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Hardcover. Condition: Brand New. 300 pages. 10.00x7.00x10.08 inches. In Stock.
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Condition: New. Print on Demand.
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Planning with Markov Decision Processes
Language: English
Published by Springer International Publishing Jul 2012, 2012
ISBN 10: 3031004310 ISBN 13: 9783031004315
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Markov Decision Processes (MDPs) are widely popular in Artificial Intelligence for modeling sequential decision-making scenarios with probabilistic dynamics. They are the framework of choice when designing an intelligent agent that needs to act for long periods of time in an environment where its actions could have uncertain outcomes. MDPs are actively researched in two related subareas of AI, probabilistic planning and reinforcement learning. Probabilistic planning assumes known models for the agent's goals and domain dynamics, and focuses on determining how the agent should behave to achieve its objectives. On the other hand, reinforcement learning additionally learns these models based on the feedback the agent gets from the environment. This book provides a concise introduction to the use of MDPs for solving probabilistic planning problems, with an emphasis on the algorithmic perspective. It covers the whole spectrum of the field, from the basics to state-of-the-art optimal and approximation algorithms. We first describe the theoretical foundations of MDPs and the fundamental solution techniques for them. We then discuss modern optimal algorithms based on heuristic search and the use of structured representations. A major focus of the book is on the numerous approximation schemes for MDPs that have been developed in the AI literature. These include determinization-based approaches, sampling techniques, heuristic functions, dimensionality reduction, and hierarchical representations. Finally, we briefly introduce several extensions of the standard MDP classes that model and solve even more complex planning problems. Table of Contents: Introduction / MDPs / Fundamental Algorithms / Heuristic Search Algorithms / Symbolic Algorithms / Approximation Algorithms / Advanced Notes 212 pp. Englisch.
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Condition: New. PRINT ON DEMAND.
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Planning with Markov Decision Processes
Language: English
Published by Springer, Berlin|Springer International Publishing|Morgan & Claypool|Springer, 2012
ISBN 10: 3031004310 ISBN 13: 9783031004315
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Markov Decision Processes (MDPs) are widely popular in Artificial Intelligence for modeling sequential decision-making scenarios with probabilistic dynamics. They are the framework of choice when designing an intelligent agent that needs to act for long per.
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Paperback. Condition: Brand New. 220 pages. 9.25x7.50x0.51 inches. In Stock. This item is printed on demand.
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Placentitis and Perinatal Infections
Language: English
Published by Springer Verlag GmbH, 2025
ISBN 10: 3031805526 ISBN 13: 9783031805523
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.
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Condition: New. Print on Demand.
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Condition: New. PRINT ON DEMAND.
