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IJCAI
2007
13 years 9 months ago
Transfer Learning in Real-Time Strategy Games Using Hybrid CBR/RL
The goal of transfer learning is to use the knowledge acquired in a set of source tasks to improve performance in a related but previously unseen target task. In this paper, we pr...
Manu Sharma, Michael P. Holmes, Juan Carlos Santam...
ICAC
2006
IEEE
14 years 1 months ago
A Hybrid Reinforcement Learning Approach to Autonomic Resource Allocation
— Reinforcement Learning (RL) provides a promising new approach to systems performance management that differs radically from standard queuing-theoretic approaches making use of ...
Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mo...
AAAI
2008
13 years 10 months ago
Potential-based Shaping in Model-based Reinforcement Learning
Potential-based shaping was designed as a way of introducing background knowledge into model-free reinforcement-learning algorithms. By identifying states that are likely to have ...
John Asmuth, Michael L. Littman, Robert Zinkov
IJAIT
2008
146views more  IJAIT 2008»
13 years 7 months ago
Learning to Behave in Space: a Qualitative Spatial Representation for Robot Navigation with Reinforcement Learning
ion mechanism to create a representation of space consisting of the circular order of detected landmarks and the relative position of walls towards the agent's moving directio...
Lutz Frommberger
KI
2007
Springer
14 years 1 months ago
Making a Robot Learn to Play Soccer Using Reward and Punishment
In this paper, we show how reinforcement learning can be applied to real robots to achieve optimal robot behavior. As example, we enable an autonomous soccer robot to learn interce...
Heiko Müller, Martin Lauer, Roland Hafner, Sa...