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» Learning the required number of agents for complex tasks
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AAAI
2008
15 years 8 months ago
POIROT - Integrated Learning of Web Service Procedures
POIROT is an integration framework for combining machine learning mechanisms to learn hierarchical models of web services procedures from a single or very small set of demonstrati...
Mark H. Burstein, Robert Laddaga, David McDonald, ...
SMC
2007
IEEE
102views Control Systems» more  SMC 2007»
16 years 10 days ago
An improved immune Q-learning algorithm
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
BICA
2010
15 years 1 months ago
Application Feedback in Guiding a Deep-Layered Perception Model
Deep-layer machine learning architectures continue to emerge as a promising biologically-inspired framework for achieving scalable perception in artificial agents. State inference ...
Itamar Arel, Shay Berant
ALIFE
2005
15 years 6 months ago
Transient Phenomena in Learning and Evolution: Genetic Assimilation and Genetic Redistribution
Deacon has recently proposed that complexes of genes can be integrated into functional groups as a result of environmental changes that mask and unmask selection pressures. For exa...
Janet Wiles, James Watson, Bradley Tonkes, Terrenc...
ECML
2003
Springer
15 years 11 months ago
Pairwise Preference Learning and Ranking
We consider supervised learning of a ranking function, which is a mapping from instances to total orders over a set of labels (options). The training information consists of exampl...
Johannes Fürnkranz, Eyke Hüllermeier