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

Jin, Nanlin and Tsang, Edward (2005) Co-evolutionary Strategies for an Alternating-Offer Bargaining Problem. In: IEEE Symposium on Computational Intelligence and Games, 4 - 6 April 2005, Essex University.

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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.

Item Type: Conference or Workshop Item (Paper)
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Related URLs:
Depositing User: Becky Skoyles
Date Deposited: 11 Aug 2014 11:56
Last Modified: 13 Oct 2019 00:24

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