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» A New Way to Introduce Knowledge into Reinforcement Learning
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GPEM
2002
104views more  GPEM 2002»
14 years 11 months ago
Genetic Programming-based Construction of Features for Machine Learning and Knowledge Discovery Tasks
In this paper we use genetic programming for changing the representation of the input data for machine learners. In particular, the topic of interest here is feature construction i...
Krzysztof Krawiec
MCS
2005
Springer
15 years 5 months ago
Ensemble of SVMs for Incremental Learning
Support Vector Machines (SVMs) have been successfully applied to solve a large number of classification and regression problems. However, SVMs suffer from the catastrophic forgetti...
Zeki Erdem, Robi Polikar, Fikret S. Gürgen, N...
ATAL
2009
Springer
15 years 6 months ago
State-coupled replicator dynamics
This paper introduces a new model, i.e. state-coupled replicator dynamics, expanding the link between evolutionary game theory and multiagent reinforcement learning to multistate ...
Daniel Hennes, Karl Tuyls, Matthias Rauterberg
ENTCS
2006
103views more  ENTCS 2006»
14 years 11 months ago
Static Equivalence is Harder than Knowledge
There are two main ways of defining secrecy of cryptographic protocols. The first version checks if the adversary can learn the value of a secret parameter. In the second version,...
Johannes Borgström
HICSS
2000
IEEE
172views Biometrics» more  HICSS 2000»
15 years 4 months ago
Sustained Knowledge Management by Organizational Culture
Preserving and fostering knowledge is the vital interest of a network-like virtual organization. The decentralized and geographically distributed organizational structure inhibits...
Birgit Lemken, Helge Kahler, Markus Rittenbruch