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» Learning Heuristic Functions from Relaxed Plans
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CEC
2011
IEEE
14 years 4 months ago
Stochastic Natural Gradient Descent by estimation of empirical covariances
—Stochastic relaxation aims at finding the minimum of a fitness function by identifying a proper sequence of distributions, in a given model, that minimize the expected value o...
Luigi Malagò, Matteo Matteucci, Giovanni Pi...
AH
2004
Springer
15 years 9 months ago
The Personal Reader: Personalizing and Enriching Learning Resources Using Semantic Web Technologies.
Traditional adaptive hypermedia systems have focused on providing adaptation functionality on a closed corpus, while Web search interfaces have delivered non-personalized informati...
Peter Dolog, Nicola Henze, Wolfgang Nejdl, Michael...
ML
2002
ACM
123views Machine Learning» more  ML 2002»
15 years 4 months ago
Feature Generation Using General Constructor Functions
Most classification algorithms receive as input a set of attributes of the classified objects. In many cases, however, the supplied set of attributes is not sufficient for creatin...
Shaul Markovitch, Dan Rosenstein
CLIMA
2004
15 years 5 months ago
Learning in BDI Multi-agent Systems
Abstract. This paper deals with the issue of learning in multi-agent systems (MAS). Particularly, we are interested in BDI (Belief, Desire, Intention) agents. Despite the relevance...
Alejandro Guerra-Hernández, Amal El Fallah-...
ICRA
2009
IEEE
170views Robotics» more  ICRA 2009»
15 years 11 months ago
Path diversity is only part of the problem
— The goal of motion planning is to find a feasible path that connects two positions and is free from collision with obstacles. Path sets are a robust approach to this problem i...
Ross A. Knepper, Matthew T. Mason