Multi-Agent Teamwork, Adaptive Learning and Adversarial Planning in Robocup Using a PRS Architecture
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{bersano-begey:1997:,
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author = "Tommaso F. Bersano-Begey and Patrick G. Kenny and
Edmund H. Durfee",
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title = "Multi-Agent Teamwork, Adaptive Learning and
Adversarial Planning in Robocup Using a PRS
Architecture",
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booktitle = "IJCAI97",
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year = "1997",
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note = "accepted",
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keywords = "genetic algorithms, genetic programming",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.53.1962",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=BC06E9197308E7FDF6E8347CECE81DC1?doi=10.1.1.53.1962&rep=rep1&type=pdf",
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size = "7 pages",
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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",
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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
Citations