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» A New Way to Introduce Knowledge into Reinforcement Learning
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ICTAI
2003
IEEE
13 years 10 months ago
Q-Concept-Learning: Generalization with Concept Lattice Representation in Reinforcement Learning
One of the very interesting properties of Reinforcement Learning algorithms is that they allow learning without prior knowledge of the environment. However, when the agents use al...
Marc Ricordeau
AAAI
2008
13 years 7 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
WEBNET
1998
13 years 6 months ago
Intelligent Knowledge Gathering and Management as New Ways of an Improved Learning Process
: This paper gives a short description of a working prototype of an intelligent background knowledge broker as an enhancement module of the Web base training system GENTLE [Maurer ...
Thomas Dietinger, Christian Gütl, Hermann A. ...
WIKIS
2009
ACM
13 years 10 months ago
Understanding learning: the Wiki way
Learning “the wiki way”, learning through wikis is a form of selfregulated learning that is independent of formal learning settings and takes place in a community of knowledge...
Joachim Kimmerle, Johannes Moskaliuk, Ulrike Cress
ICML
1998
IEEE
14 years 6 months ago
RL-TOPS: An Architecture for Modularity and Re-Use in Reinforcement Learning
This paper introduces the RL-TOPs architecture for robot learning, a hybrid system combining teleo-reactive planning and reinforcement learning techniques. The aim of this system ...
Malcolm R. K. Ryan, Mark D. Pendrith