Multi-Agent Teamwork, Adaptive Learning and Adversarial Planning in Robocup Using a PRS Architecture

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{bersano-begey:1997:,

• author = "Tommaso F. Bersano-Begey and Patrick G. Kenny and Edmund H. Durfee",
• title = "Multi-Agent Teamwork, Adaptive Learning and Adversarial Planning in Robocup Using a PRS Architecture",
• booktitle = "IJCAI97",
• year = "1997",
• note = "accepted",
• keywords = "genetic algorithms, genetic programming",
• URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.53.1962",
• URL = "http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=BC06E9197308E7FDF6E8347CECE81DC1?doi=10.1.1.53.1962&rep=rep1&type=pdf",
• size = "7 pages",
• abstract = "Our approach for the Robocup97 competition is to emphasise teamwork among agents by augmenting reactions (based on awareness of the current situation) with predictions (based on predefined multiagent manoeuvres). These predictions are accomplished by allowing agents to cooperatively accomplish predefined plans, which are elaborated reactively and hierarchically to ensure responsiveness to changing circumstances. By supporting the runtime construction of plans, our approach simplifies the introduction of new plans, strategies, and actions, and produces a framework for dynamic adaptation and plan recognition through automatically generating belief networks. Our implementation is built on top of UM-PRS, a procedural reasoning system architecture for real-time environments, which allows specifying, executing, and integrating plans based on subgoaling and preconditions",
• notes = "um-prs.pdf broken 5-sep-97 http://www.sonycsl.co.jp/person/kitano/RoboCup/ws97.html",

}

Genetic Programming entries for Tommaso F Bersano-Begey Patrick G Kenny Edmund H Durfee

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