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» Learning Heuristic Functions from Relaxed Plans
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CEC
2011
IEEE
13 years 9 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 3 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»
14 years 9 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
14 years 11 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 4 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