Learning IPD strategies through co-evolution

Siang Yew CHONG; Jan HUMBLE; Graham KENDALL; Jiawei LI; Xin YAO

doi:10.1142/9789812770684_0003

Learning IPD strategies through co-evolution

Siang Yew CHONG, Jan HUMBLE, Graham KENDALL, Jiawei LI, Xin YAO

Research output: Book Chapters | Papers in Conference Proceedings › Book Chapter › Research › peer-review

4 Citations (Scopus)

Abstract

The following sections are included:
• Introduction
• Co-evolving Strategies for the IPD Game
-Co-evolutionary Learning Framework
-Shadow of the Future
-Issues for Co-evolutionary Learning of IPD Strategies
• Extending the IPD Game
-Extending the IPD with More Choices
-IPD with Noise
-N-Player IPD
-Other Extensions
• Conclusion and Future Directions
• References.
© 2007 by World Scientific Publishing Co. Pte. Ltd.

Original language	English
Title of host publication	The Iterated Prisoners' Dilemma : 20 Years On
Editors	Graham KENDALL, Xin YAO, Siang Yew CHONG
Publisher	World Scientific Publishing Co.
Chapter	3
Pages	63-87
Number of pages	25
ISBN (Print)	9789812770684
DOIs	https://doi.org/10.1142/9789812770684_0003
Publication status	Published - May 2007
Externally published	Yes

Publication series

Name	Advances in Natural Computation
Publisher	World Scientific Publishing Co.
Volume	4
ISSN (Print)	2010-295X

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10.1142/9789812770684_0003

Cite this

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title = "Learning IPD strategies through co-evolution",

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author = "CHONG, {Siang Yew} and Jan HUMBLE and Graham KENDALL and Jiawei LI and Xin YAO",

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Learning IPD strategies through co-evolution. / CHONG, Siang Yew; HUMBLE, Jan; KENDALL, Graham et al.
The Iterated Prisoners' Dilemma : 20 Years On. ed. / Graham KENDALL; Xin YAO; Siang Yew CHONG. World Scientific Publishing Co., 2007. p. 63-87 (Advances in Natural Computation; Vol. 4).

Research output: Book Chapters | Papers in Conference Proceedings › Book Chapter › Research › peer-review

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AU - LI, Jiawei

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AB - The following sections are included: • Introduction • Co-evolving Strategies for the IPD Game -Co-evolutionary Learning Framework -Shadow of the Future -Issues for Co-evolutionary Learning of IPD Strategies • Extending the IPD Game -Extending the IPD with More Choices -IPD with Noise -N-Player IPD -Other Extensions • Conclusion and Future Directions • References. © 2007 by World Scientific Publishing Co. Pte. Ltd.

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Learning IPD strategies through co-evolution

Abstract

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The iterated prisoners’ dilemma : 20 years on

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