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AAAI
2007
15 years 7 months ago
A Robot That Uses Existing Vocabulary to Infer Non-Visual Word Meanings from Observation
The authors present TWIG, a visually grounded wordlearning system that uses its existing knowledge of vocabulary, grammar, and action schemas to help it learn the meanings of new ...
Kevin Gold, Brian Scassellati
IJCAI
2001
15 years 6 months ago
Representing Sentence Structure in Hidden Markov Models for Information Extraction
We study the application of Hidden Markov Models (HMMs) to learning information extractors for
Soumya Ray, Mark Craven
JAIR
2010
131views more  JAIR 2010»
15 years 3 months ago
Automatic Induction of Bellman-Error Features for Probabilistic Planning
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
Jia-Hong Wu, Robert Givan
AAMAS
2007
Springer
15 years 11 months ago
Bifurcation Analysis of Reinforcement Learning Agents in the Selten's Horse Game
Abstract. The application of reinforcement learning algorithms to multiagent domains may cause complex non-convergent dynamics. The replicator dynamics, commonly used in evolutiona...
Alessandro Lazaric, Jose Enrique Munoz de Cote, Fa...
AIHC
2007
Springer
15 years 11 months ago
Emotion and Reinforcement: Affective Facial Expressions Facilitate Robot Learning
Computer models can be used to investigate the role of emotion in learning. Here we present EARL, our framework for the systematic study of the relation between emotion, adaptation...
Joost Broekens