Co-evolutionary Strategies for an Alternating-Offer Bargaining Problem.

Nanlin Jin, Edward Tsang

Research output: Contribution to conferencePaperpeer-review

7 Citations (Scopus)

Abstract

In this paper, we apply an Evolutionary Algo- rithm (EA) to solve the Rubinstein's Basic Alternating- Offer Bargaining Problem, and compare our experi- mental results with its analytic game-theoretic solution. The application of EA employs an alternative set of assumptions on the players' behaviors. Experimental outcomes suggest that the applied co-evolutionary algo- rithm, one of Evolutionary Algorithms, is able to gener- ate convincing approximations of the theoretic solutions. The major advantages of EA over the game-theoretic analysis are its flexibility and ease of application to vari- ants of Rubinstein Bargaining Problems and compli- cated bargaining situations for which theoretic solutions are unavailable.
Original languageEnglish
Publication statusPublished - 2005
EventIEEE Symposium on Computational Intelligence and Games - Essex University
Duration: 1 Jan 2005 → …
http://cswww.essex.ac.uk/cig/2005/index.jsp?page=intro.html

Conference

ConferenceIEEE Symposium on Computational Intelligence and Games
Period1/01/05 → …
Internet address

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