Indirect co-evolution for understanding belief in an incomplete information dynamic game

Nanlin Jin

doi:10.1145/1143997.1144067

Indirect co-evolution for understanding belief in an incomplete information dynamic game

Nanlin Jin^*

^*Corresponding author for this work

University of Essex

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

Abstract

This study aims to design a new co-evolution algorithm, Mixture Co-evolution which enables modeling of integration and composition of direct co-evolution and indirect co-evolution. This algorithm is applied to investigate properties of players' belief and of information incompleteness in a dynamic game.

Original language	English
Title of host publication	GECCO 2006 - Genetic and Evolutionary Computation Conference
Publisher	Association for Computing Machinery (ACM)
Pages	383-384
Number of pages	2
ISBN (Print)	1595931864, 9781595931863
DOIs	https://doi.org/10.1145/1143997.1144067
Publication status	Published - 2006
Externally published	Yes
Event	8th Annual Genetic and Evolutionary Computation Conference 2006 - Seattle, WA, United States Duration: 8 Jul 2006 → 12 Jul 2006

Publication series

Name	GECCO 2006 - Genetic and Evolutionary Computation Conference
Volume	1

Conference

Conference	8th Annual Genetic and Evolutionary Computation Conference 2006
Country/Territory	United States
City	Seattle, WA
Period	8/07/06 → 12/07/06

Keywords

Belief
Co-evolution
Game theory
Incomplete Information

Access to Document

10.1145/1143997.1144067

Cite this

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title = "Indirect co-evolution for understanding belief in an incomplete information dynamic game",

abstract = "This study aims to design a new co-evolution algorithm, Mixture Co-evolution which enables modeling of integration and composition of direct co-evolution and indirect co-evolution. This algorithm is applied to investigate properties of players' belief and of information incompleteness in a dynamic game.",

keywords = "Belief, Co-evolution, Game theory, Incomplete Information",

author = "Nanlin Jin",

year = "2006",

doi = "10.1145/1143997.1144067",

language = "English",

isbn = "1595931864",

series = "GECCO 2006 - Genetic and Evolutionary Computation Conference",

publisher = "Association for Computing Machinery (ACM)",

pages = "383--384",

booktitle = "GECCO 2006 - Genetic and Evolutionary Computation Conference",

note = "8th Annual Genetic and Evolutionary Computation Conference 2006 ; Conference date: 08-07-2006 Through 12-07-2006",

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Jin, N 2006, Indirect co-evolution for understanding belief in an incomplete information dynamic game. in GECCO 2006 - Genetic and Evolutionary Computation Conference. GECCO 2006 - Genetic and Evolutionary Computation Conference, vol. 1, Association for Computing Machinery (ACM), pp. 383-384, 8th Annual Genetic and Evolutionary Computation Conference 2006, Seattle, WA, United States, 8/07/06. https://doi.org/10.1145/1143997.1144067

Indirect co-evolution for understanding belief in an incomplete information dynamic game. / Jin, Nanlin.
GECCO 2006 - Genetic and Evolutionary Computation Conference. Association for Computing Machinery (ACM), 2006. p. 383-384 (GECCO 2006 - Genetic and Evolutionary Computation Conference; Vol. 1).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

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AB - This study aims to design a new co-evolution algorithm, Mixture Co-evolution which enables modeling of integration and composition of direct co-evolution and indirect co-evolution. This algorithm is applied to investigate properties of players' belief and of information incompleteness in a dynamic game.

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KW - Game theory

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SN - 9781595931863

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BT - GECCO 2006 - Genetic and Evolutionary Computation Conference

PB - Association for Computing Machinery (ACM)

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Indirect co-evolution for understanding belief in an incomplete information dynamic game

Abstract

Publication series

Conference

Keywords

Access to Document

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