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Towards a Life-Long Learning Soccer Agent
2002 (English)In: In RoboCup 2002: Robot Soccer World Cup VI, 2002, Vol. 2752, 126-134Konferensbidrag (Refereed)
Abstract [en]

One problem in robotic soccer (and in robotics in general) is to adapt skills and the overall behavior to a changing environment and to hardware improvements. We applied hierarchical reinforcement learning in an SMDP framework learning on all levels simultaneously. As our experiments show, learning simultaneously on the skill level and on the skill selection level is advantageous since it allows for a smooth adaption to a changing environment. Furthermore, the skills we trained turn also out to be quite competitive when run on the real robotic players of the players of our CS Freiburg team.

National Category
Robotics
Identifiers
urn:nbn:se:liu:diva-72554 (URN)oai:DiVA.org:liu-72554 (OAI)
Projects
Artificial Intelligence & Integrated Computer Systems
Available from2011-11-28 Created:2011-11-28 Last updated:2011-12-01

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Kleiner, AlexanderDietl, M.Nebel, Bernhard
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University of Freiburg
Robotics

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