# Evolving a Team

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## Haynes, T., Sen, S., Schoenefeld, D. and Wainwright, R.

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 Info: Working Notes for the AAAI Symposium on Genetic Programming (Conference proceedings), 1995, p. 23-30 Keywords: genetic algorithms, genetic programming Abstract: We introduce a cooperative co--evolutionary system to facilitate the development of teams of agents. Specifically, we deal with the credit assignment problem [CA] of how to fairly split the fitness of a team to all of its participants. We believe that $k$ different strategies for controlling the actions of a group of $k$ agents can combine to form a cooperation strategy which efficiently results in attaining a global goal. A concern is the amount of time needed to either evolve a good team or reach convergence. We present several crossover mechanisms to reduce this time. Even with this mechanisms, the time is large; which precluded the gathering of sufficient data for a statistical base. Notes: AAAI-95f GP {\em Telephone:} 415-328-3123 {\em Fax:} 415-321-4457 {\em email} info@aaai.org {\em URL:} http://www.aaai.org/ Internet search: Search GoogleSearch Google ScholarSearch Citeseer using GoogleSearch Google for PDFSearch Google Scholar for PDFSearch Citeseer for PDF using Google Review item: Mark as doublet (will be reviewed)

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BibTex:
 @InProceedings{Haynes95:Team, author = "Thomas Haynes and Sandip Sen and Dale Schoenefeld and Roger Wainwright", title = "Evolving a Team", booktitle = "Working Notes for the AAAI Symposium on Genetic Programming", year = "1995", editor = "E. V. Siegel and J. R. Koza", pages = "23--30", address = "MIT, Cambridge, MA, USA", publisher_address = "445 Burgess Drive, Menlo Park, CA 94025, USA", month = "10--12 " # nov, publisher = "AAAI", keywords = "genetic algorithms, genetic programming", abstract = "We introduce a cooperative co--evolutionary system to facilitate the development of teams of agents. Specifically, we deal with the credit assignment problem of how to fairly split the fitness of a team to all of its participants. We believe that ${k}$ different strategies for controlling the actions of a group of ${k}$ agents can combine to form a cooperation strategy which efficiently results in attaining a global goal. A concern is the amount of time needed to either evolve a good team or reach convergence. We present several crossover mechanisms to reduce this time. Even with this mechanisms, the time is large; which precluded the gathering of sufficient data for a statistical base.", notes = "AAAI-95f GP {\em Telephone:} 415-328-3123 {\em Fax:} 415-321-4457 {\em email} info@aaai.org {\em URL:} http://www.aaai.org/", }