311 search results - page 2 / 63 » Learning first-order probabilistic models with combining rul... |
ICMLA
2009
13 years 3 months ago
2009
Languages that combine predicate logic with probabilities are needed to succinctly represent knowledge in many real-world domains. We consider a formalism based on universally qua...
ICML
2005
IEEE
14 years 6 months ago
2005
IEEE
Many real-world domains exhibit rich relational structure and stochasticity and motivate the development of models that combine predicate logic with probabilities. These models de...
SDM
2010
SIAM
13 years 6 months ago
2010
SIAM
A relational probability tree (RPT) is a type of decision tree that can be used for probabilistic classification of instances with a relational structure. Each leaf of an RPT cont...
JAIR
2010
13 years 3 months ago
2010
Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
ICMLA
2010
13 years 2 months ago
2010
Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...