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NIPS
2008
15 years 6 months ago
A rational model of preference learning and choice prediction by children
Young children demonstrate the ability to make inferences about the preferences of other agents based on their choices. However, there exists no overarching account of what childr...
Christopher G. Lucas, Thomas L. Griffiths, Fei Xu,...
IJCAI
1989
15 years 5 months ago
Learning Novel Domains Through Curiosity and Conjecture
This paper describes DIDO, a system we have developed to carry out exploratory learning of unfamiliar domains without assistance from an external teacher. The program incorporates...
Paul D. Scott, Shaul Markovitch
ICANN
2010
Springer
15 years 5 months ago
Reinforcement Learning Based Neural Controllers for Dynamic Processes without Exploration
Abstract. In this paper we present a Reinforcement Learning (RL) approach with the capability to train neural adaptive controllers for complex control problems without expensive on...
Frank-Florian Steege, André Hartmann, Erik ...
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JAIR
2002
120views more  JAIR 2002»
15 years 4 months ago
Learning Geometrically-Constrained Hidden Markov Models for Robot Navigation: Bridging the Topological-Geometrical Gap
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
Hagit Shatkay, Leslie Pack Kaelbling
CVPR
2003
IEEE
16 years 6 months ago
Object Class Recognition by Unsupervised Scale-Invariant Learning
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
Robert Fergus, Pietro Perona, Andrew Zisserman