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ECSQARU
2009
Springer
14 years 11 days ago
Using Transfinite Ordinal Conditional Functions
Abstract. Ordinal Conditional Functions (OCFs) are one of the predominant frameworks to define belief change operators. In his original paper Spohn defines OCFs as functions from t...
Sébastien Konieczny
AI
2006
Springer
14 years 7 days ago
Belief Selection in Point-Based Planning Algorithms for POMDPs
Abstract. Current point-based planning algorithms for solving partially observable Markov decision processes (POMDPs) have demonstrated that a good approximation of the value funct...
Masoumeh T. Izadi, Doina Precup, Danielle Azar
AAAI
2006
13 years 10 months ago
Sound and Efficient Inference with Probabilistic and Deterministic Dependencies
Reasoning with both probabilistic and deterministic dependencies is important for many real-world problems, and in particular for the emerging field of statistical relational lear...
Hoifung Poon, Pedro Domingos
ECSQARU
2001
Springer
14 years 1 months ago
The Search of Causal Orderings: A Short Cut for Learning Belief Networks
Abstract. Although we can build a belief network starting from any ordering of its variables, its structure depends heavily on the ordering being selected: the topology of the netw...
Silvia Acid, Luis M. de Campos, Juan F. Huete
CORR
2008
Springer
94views Education» more  CORR 2008»
13 years 8 months ago
Decision Support with Belief Functions Theory for Seabed Characterization
The seabed characterization from sonar images is a very hard task because of the produced data and the unknown environment, even for an human expert. In this work we propose an ori...
Arnaud Martin, Isabelle Quidu