On-the-fly generation of multi-robot team formation strategies based on game conditions

John Atkinson, Dario Rojas

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


This paper describes a new model to automatically generating dynamic formation strategies for robotic soccer applications based on game conditions, regarded to as favorable or unfavorable for a robotic team. Decisions are distributedly computed by the players of a multi-agent team. A game policy is defined and applied by a human coach who establishes the attitude of the team for defending or attacking. A simple neural net model is applied using current and previous game experience to classify the game's parameters so that the new game conditions can be determined so that a robotic team can modify its strategy on-the-fly. Experiments and results of the proposed model for a robotic soccer team show the promise of the approach.

Original languageEnglish
Pages (from-to)6082-6090
Number of pages9
JournalExpert Systems with Applications
Issue number3 PART 2
StatePublished - Apr 2009
Externally publishedYes


  • Multi-agent systems
  • Robotics game strategies
  • Robotics soccer
  • Team formation


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