Relative Fitness and Absolute Fitness for Co-evolutionary Systems

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{eurogp:JinT05,

• author = "Nanlin Jin and Edward P. K. Tsang",
• editor = "Maarten Keijzer and Andrea Tettamanzi and Pierre Collet and Jano I. {van Hemert} and Marco Tomassini",
• title = "Relative Fitness and Absolute Fitness for Co-evolutionary Systems",
• booktitle = "Proceedings of the 8th European Conference on Genetic Programming",
• publisher = "Springer",
• series = "Lecture Notes in Computer Science",
• volume = "3447",
• year = "2005",
• address = "Lausanne, Switzerland",
• month = "30 " # mar # " - 1 " # apr,
• organisation = "EvoNet",
• keywords = "genetic algorithms, genetic programming: Poster",
• ISBN = "3-540-25436-6",
• pages = "331--340",
• DOI = "doi:10.1007/978-3-540-31989-4_30",
• DOI = "doi:10.1007/b107383",
• bibsource = "DBLP, http://dblp.uni-trier.de",
• abstract = "The commonly adopted fitness which evaluates the performance of individuals in co-evolutionary systems is relative fitness. Relative fitness is a dynamic assessment subject to the other co-evolving population(s). Researchers apparently pay less attention to the use of absolute fitness functions in studying co-evolutionary algorithms than the use of relative fitness functions. One of our aims in this work is to formalise both relative fitness and absolute fitness for co-evolving systems. Another aim is to demonstrate the usage of absolute and relative fitness through a case study. We develop a co-evolutionary system by means of Genetic Programming to discover co-adapted strategies for a Basic Alternating-Offers Bargaining Problem. In this case, the relative fitness essentially drives co-evolution to converge to game-theoretic equilibrium. Whereas the relative fitness alone can not discover the whole view of co-evolutionary progress. The absolute fitness, on the other hand helps us to monitor the development of co-adaptive learning. Having analysed the micro-behaviour of the players' strategies, based on their absolute fitness, we can explain how the co-evolving populations converge to the perfect equilibria.",
• notes = "Part of \cite{keijzer:2005:GP} EuroGP'2005 held in conjunction with EvoCOP2005 and EvoWorkshops2005",

}

Genetic Programming entries for Nanlin Jin Edward P K Tsang

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