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ICML
2009
IEEE
14 years 8 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint
AGENTS
1998
Springer
13 years 11 months ago
Learning Situation-Dependent Costs: Improving Planning from Probabilistic Robot Execution
Physical domains are notoriously hard to model completely and correctly, especially to capture the dynamics of the environment. Moreover, since environments change, it is even mor...
Karen Zita Haigh, Manuela M. Veloso
ICML
1996
IEEE
14 years 8 months ago
Representing and Learning Quality-Improving Search Control Knowledge
Generating good, production-quality plans is an essential element in transforming planners from research tools into real-world applications, but one that has been frequently overl...
M. Alicia Pérez
FLAIRS
2007
13 years 10 months ago
Learning Paraphrases from WNS Corpora
Paraphrase detection can be seen as the task of aligning sentences that convey the same information but yet are written in different forms. Such resources are important to automat...
João Cordeiro, Gaël Dias, Pavel Brazdi...
ACL
2006
13 years 9 months ago
Automatic Learning of Textual Entailments with Cross-Pair Similarities
In this paper we define a novel similarity measure between examples of textual entailments and we use it as a kernel function in Support Vector Machines (SVMs). This allows us to ...
Fabio Massimo Zanzotto, Alessandro Moschitti