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» A New Way to Introduce Knowledge into Reinforcement Learning
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SAB
2010
Springer
117views Optimization» more  SAB 2010»
14 years 10 months ago
Indirectly Encoding Neural Plasticity as a Pattern of Local Rules
Biological brains can adapt and learn from past experience. In neuroevolution, i.e. evolving artificial neural networks (ANNs), one way that agents controlled by ANNs can evolve t...
Sebastian Risi, Kenneth O. Stanley
ICDM
2007
IEEE
184views Data Mining» more  ICDM 2007»
15 years 6 months ago
Bayesian Folding-In with Dirichlet Kernels for PLSI
Probabilistic latent semantic indexing (PLSI) represents documents of a collection as mixture proportions of latent topics, which are learned from the collection by an expectation...
Alexander Hinneburg, Hans-Henning Gabriel, Andr&eg...
AINA
2009
IEEE
15 years 6 months ago
SOA Initiatives for eLearning: A Moodle Case
— Mobile learning applications introduce a new degree of ubiquitousness in the learning process. There is a new generation of ICT-powered mobile learning experiences that exist i...
María José Casany Guerrero, Marc Ali...
EPS
1998
Springer
15 years 4 months ago
Evolving Heuristics for Planning
Abstract. In this paper we describe EvoCK, a new approach to the application of genetic programming (GP) to planning. This approach starts with a traditional AI planner (PRODIGY)an...
Ricardo Aler, Daniel Borrajo, Pedro Isasi
CVPR
2010
IEEE
15 years 6 months ago
Putting local features on a Manifold
Local features have proven very useful for recognition. Manifold learning has proven to be a very powerful tool in data analysis. However, manifold learning application for imag...
Marwan Torki and Ahmed Elgammal