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» Coordinated Reinforcement Learning
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ACSAC
2005
IEEE
15 years 10 months ago
Generating Policies for Defense in Depth
Coordinating multiple overlapping defense mechat differing levels of abstraction, is fraught with the potential for misconfiguration, so there is strong motivation to generate p...
Paul Rubel, Michael Ihde, Steven Harp, Charles Pay...
CIA
2006
Springer
15 years 8 months ago
Market-Inspired Approach to Collaborative Learning
The paper describes a decentralized peer-to-peer multi-agent learning method based on inductive logic programming and knowledge trading. The method uses first-order logic for model...
Jan Tozicka, Michal Jakob, Michal Pechoucek
ICML
2008
IEEE
16 years 5 months ago
Sample-based learning and search with permanent and transient memories
We present a reinforcement learning architecture, Dyna-2, that encompasses both samplebased learning and sample-based search, and that generalises across states during both learni...
David Silver, Martin Müller 0003, Richard S. ...
ATAL
2008
Springer
15 years 6 months ago
Adaptive Kanerva-based function approximation for multi-agent systems
In this paper, we show how adaptive prototype optimization can be used to improve the performance of function approximation based on Kanerva Coding when solving largescale instanc...
Cheng Wu, Waleed Meleis
SIGCSE
2009
ACM
119views Education» more  SIGCSE 2009»
16 years 4 months ago
Implications of integrating test-driven development into CS1/CS2 curricula
Many academic and industry professionals have called for more testing in computer science curricula. Test-driven development (TDD) has been proposed as a solution to improve testi...
Chetan Desai, David S. Janzen, John Clements