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PKDD
2009
Springer
181views Data Mining» more  PKDD 2009»
14 years 2 months ago
Active Learning for Reward Estimation in Inverse Reinforcement Learning
Abstract. Inverse reinforcement learning addresses the general problem of recovering a reward function from samples of a policy provided by an expert/demonstrator. In this paper, w...
Manuel Lopes, Francisco S. Melo, Luis Montesano
ATAL
2006
Springer
13 years 11 months ago
Rule value reinforcement learning for cognitive agents
RVRL (Rule Value Reinforcement Learning) is a new algorithm which extends an existing learning framework that models the environment of a situated agent using a probabilistic rule...
Christopher Child, Kostas Stathis
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
14 years 8 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
ATAL
2006
Springer
13 years 11 months ago
Ontology-guided learning to improve communication between groups of agents
We present a general method for agents using ontologies as part of their knowledge representation to teach each other concepts to improve their communication and thus cooperation ...
Mohsen Afsharchi, Behrouz H. Far, Jörg Denzin...
LREC
2008
123views Education» more  LREC 2008»
13 years 9 months ago
An Economic View on Human Language Technology Evaluation
This paper analyses some general issues about human language technology evaluation, focusing on economic aspects. It first provides a scientific rationale for the need to organize...
Edouard Geoffrois