Generating dynamic formation strategies based on human experience and game conditions

John Atkinson, Dario Rojas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


In this paper, a new approach to automatically generating game strategies based on the game conditions is presented. 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. Results of the implemented model for a robotic soccer team are discussed.

Original languageEnglish
Title of host publicationRoboCup 2007
Subtitle of host publicationRobot Soccer World Cup XI
Number of pages12
StatePublished - 2008
Externally publishedYes
Event11th RoboCup International Symposium, RoboCup 2007 - Atlanta, GA, United States
Duration: 9 Jul 200710 Jul 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5001 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th RoboCup International Symposium, RoboCup 2007
Country/TerritoryUnited States
CityAtlanta, GA


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


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