Reinforcement Learning

Reinforcement Learning

An Introduction

eBook - 1998
Rate this:
MIT Press

Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.

The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.


Richard Sutton and Andrew Barto provide a clear and simple account of the key ideasand algorithms of reinforcement learning. Their discussion ranges from the history of the field'sintellectual foundations to the most recent developments and applications.



Publisher: Cambridge, Mass. : MIT Press, c1998
ISBN: 9780585024455
0585024456
0262193981
Characteristics: 1 online resource (xviii, 322 p.) : ill
Additional Contributors: Barto, Andrew G.

Opinion

From the critics


Community Activity

Comment

Add a Comment

There are no comments for this title yet.

Age Suitability

Add Age Suitability

There are no age suitabilities for this title yet.

Summary

Add a Summary

There are no summaries for this title yet.

Notices

Add Notices

There are no notices for this title yet.

Quotes

Add a Quote

There are no quotes for this title yet.

Explore Further

Recommendations

Subject Headings

  Loading...

Find it at IPL

  Loading...
[]
[]
To Top