A phenotypic analysis of GP-evolved team behaviours

Created by W.Langdon from gp-bibliography.bib Revision:1.4202

  author =       "Darren Doherty and Colm O'Riordan",
  title =        "A phenotypic analysis of GP-evolved team behaviours",
  booktitle =    "GECCO '07: Proceedings of the 9th annual conference on
                 Genetic and evolutionary computation",
  year =         "2007",
  editor =       "Dirk Thierens and Hans-Georg Beyer and 
                 Josh Bongard and Jurgen Branke and John Andrew Clark and 
                 Dave Cliff and Clare Bates Congdon and Kalyanmoy Deb and 
                 Benjamin Doerr and Tim Kovacs and Sanjeev Kumar and 
                 Julian F. Miller and Jason Moore and Frank Neumann and 
                 Martin Pelikan and Riccardo Poli and Kumara Sastry and 
                 Kenneth Owen Stanley and Thomas Stutzle and 
                 Richard A Watson and Ingo Wegener",
  volume =       "2",
  isbn13 =       "978-1-59593-697-4",
  pages =        "1951--1958",
  address =      "London",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco2007/docs/p1951.pdf",
  DOI =          "doi:10.1145/1276958.1277347",
  publisher =    "ACM Press",
  publisher_address = "New York, NY, USA",
  month =        "7-11 " # jul,
  organisation = "ACM SIGEVO (formerly ISGEC)",
  keywords =     "genetic algorithms, genetic programming, Real-World
                 Applications, AI, artificial intelligence, cooperative
                 agents, phenotypic analysis, tactical team behaviour",
  abstract =     "This paper presents an approach to analyse the
                 behaviours of teams of autonomous agents who work
                 together to achieve a common goal. The agents in a team
                 are evolved together using a genetic programming (GP)
                 [8] approach where each team of agents is represented
                 as a single GP tree or chromosome. A number of such
                 teams are evolved and their behaviours analysed in an
                 attempt to identify combinations of individual agent
                 behaviours that constitute good (or bad) team
                 behaviour. For each team we simulate a number of games
                 and periodically capture the agents' behavioural
                 information from the gaming environment during each
                 simulation. This information is stored in a series of
                 status records that can be later analysed. We compare
                 and contrast the behaviours of agents in the evolved
                 teams to see if there is a correlation between a team's
                 performance (fitness score) and the combined behaviours
                 of the team's agents. This approach could also be
                 applied to other GP-evolved teams in different
  notes =        "GECCO-2007 A joint meeting of the sixteenth
                 international conference on genetic algorithms
                 (ICGA-2007) and the twelfth annual genetic programming
                 conference (GP-2007).

                 ACM Order Number 910071",

Genetic Programming entries for Darren Doherty Colm O'Riordan