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» Hierarchical Memory-Based Reinforcement Learning
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AIIDE
2009
13 years 8 months ago
Examining Extended Dynamic Scripting in a Tactical Game Framework
Dynamic scripting is a reinforcement learning algorithm designed specifically to learn appropriate tactics for an agent in a modern computer game, such as Neverwinter Nights. This...
Jeremy Ludwig, Arthur Farley
ROBOCUP
2007
Springer
167views Robotics» more  ROBOCUP 2007»
14 years 1 months ago
Cooperative/Competitive Behavior Acquisition Based on State Value Estimation of Others
The existing reinforcement learning approaches have been suffering from the curse of dimension problem when they are applied to multiagent dynamic environments. One of the typical...
Kentarou Noma, Yasutake Takahashi, Minoru Asada
SARA
2005
Springer
14 years 1 months ago
The Cruncher: Automatic Concept Formation Using Minimum Description Length
Abstract. We present The Cruncher, a simple representation framework and algorithm based on minimum description length for automatically forming an ontology of concepts from attrib...
Marc Pickett, Tim Oates
AR
2008
118views more  AR 2008»
13 years 7 months ago
Efficient Behavior Learning Based on State Value Estimation of Self and Others
The existing reinforcement learning methods have been seriously suffering from the curse of dimension problem especially when they are applied to multiagent dynamic environments. ...
Yasutake Takahashi, Kentarou Noma, Minoru Asada
AAAI
1994
13 years 9 months ago
Hierarchical Chunking in Classifier Systems
Two standard schemes for learning in classifier systems have been proposed in the literature: the bucket brigade algorithm (BBA) and the profit sharing plan (PSP). The BBA is a lo...
Gerhard Weiß