Revising the Trade-off Between the Number of Agents and Agent Intelligence

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Marcus Komann and Dietmar Fey",
  title =        "Revising the Trade-off Between the Number of Agents
                 and Agent Intelligence",
  booktitle =    "EvoCOMPLEX",
  year =         "2010",
  editor =       "Cecilia {Di Chio} and Stefano Cagnoni and 
                 Carlos Cotta and Marc Ebner and Aniko Ekart and 
                 Anna I. Esparcia-Alcazar and Chi-Keong Goh and 
                 Juan J. Merelo and Ferrante Neri and Mike Preuss and 
                 Julian Togelius and Georgios N. Yannakakis",
  volume =       "6024",
  series =       "LNCS",
  pages =        "31--40",
  address =      "Istanbul",
  month =        "7-9 " # apr,
  organisation = "EvoStar",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, finite state
  isbn13 =       "978-3-642-12238-5",
  DOI =          "doi:10.1007/978-3-642-12239-2_4",
  size =         "10 pages",
  abstract =     "Emergent agents are a promising approach to handle
                 complex systems. Agent intelligence is thereby either
                 defined by the number of states and the state
                 transition function or the length of their steering
                 programs. Evolution has shown to be successful in
                 creating desired behaviors for such agents. Genetic
                 algorithms have been used to find agents with fixed
                 numbers of states and genetic programming is able to
                 balance between the steering program length and the
                 costs for longer programs. This paper extends previous
                 work by further discussing the relationship between
                 either using more agents with less intelligence or
                 using fewer agents with higher intelligence. Therefore,
                 the Creatures' Exploration Problem with a complex input
                 set is solved by evolving emergent agents. It shows
                 that neither a sole increase in intelligence nor amount
                 is the best solution. Instead, a cautious balance
                 creates best results.",
  notes =        "EvoCOMPLEX'2010 held in conjunction with EuroGP'2010
                 EvoCOP2010 EvoBIO2010",

Genetic Programming entries for Marcus Komann Dietmar Fey