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GECCO
2008
Springer
128views Optimization» more  GECCO 2008»
15 years 5 months ago
Adapted Pittsburgh classifier system: building accurate strategies in non markovian environments
This paper focuses on the study of the behavior of a genetic algorithm based classifier system, the Adapted Pittsburgh Classifier System (A.P.C.S), on maze type environments con...
Gilles Énée, Mathias Péroumal...
SASO
2008
IEEE
15 years 10 months ago
Leveraging Organizational Guidance Policies with Learning to Self-Tune Multiagent Systems
As organization-based multiagent systems are applied to more complex problems, configuring and tuning the systems can become nearly as complex as the original problem a system wa...
Scott J. Harmon, Scott A. DeLoach, Robby, Doina Ca...
ECAI
1994
Springer
15 years 8 months ago
Exploiting Causal Domain Knowledge for Learning to Control Dynamic Systems
This paper introduces a simple yete ective method for using causal domain knowledge for learning to control dynamic systems. Elementary qualitative causal dependencies of the domai...
Achim G. Hoffmann
ICML
2010
IEEE
15 years 5 months ago
Learning the Linear Dynamical System with ASOS
We develop a new algorithm, based on EM, for learning the Linear Dynamical System model. Called the method of Approximated Second-Order Statistics (ASOS) our approach achieves dra...
James Martens
MA
1999
Springer
87views Communications» more  MA 1999»
15 years 8 months ago
Communicating Neural Network Knowledge between Agents in a Simulated Aerial Reconnaissance System
In order to maintain their performance in a dynamic environment, agents may be required to modify their learning behavior during run-time. If an agent utilizes a rule-based system...
Stephen Quirolgico, K. Canfield, Timothy W. Finin,...