The RoboCup synthetic agent challenge 97 View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2005-07-29

AUTHORS

Hiroaki Kitano , Milind Tambe , Peter Stone , Manuela Veloso , Silvia Coradeschi , Eiichi Osawa , Hitoshi Matsubara , Itsuki Noda , Minoru Asada

ABSTRACT

RoboCup Challenge offers a set of challenges for intelligent agent researchers using a friendly competition in a dynamic, real-time, multi-agent domain. While RoboCup in general envisions longer range challenges over the next few decades, RoboCup Challenge presents three specific challenges for the next two years: (i) learning of individual agents and teams; (ii) multi-agent team planning and plan-execution in service of teamwork; and (iii) opponent modeling. RoboCup Challenge provides a novel opportunity for machine learning, planning, and multi-agent researchers — it not only supplies a concrete domain to evalute their techniques, but also challenges researchers to evolve these techniques to face key constraints fundamental to this domain: real-time, uncertainty, and teamwork. More... »

PAGES

62-73

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/3-540-64473-3_49

DOI

http://dx.doi.org/10.1007/3-540-64473-3_49

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1027773402


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