Abstract
This paper presents new results on the complexity of graph-theoretical models that represent probabilities (Bayesian networks) and that represent interval and set valued probabilities (credal networks). We define a new class of networks with bounded width, and introduce a new decision problem for Bayesian networks, the maximin a posteriori. We present new links between the Bayesian and credal networks, and present new results both for Bayesian networks (most probable explanation with observations, maximin a posteriori) and for credal networks (bounds on probabilities a posteriori, most probable explanation with and without observations, maximum a posteriori).
Original language | American English |
---|---|
Pages | 1313-1318 |
Number of pages | 6 |
State | Published - 1 Dec 2005 |
Externally published | Yes |
Event | IJCAI International Joint Conference on Artificial Intelligence - Duration: 1 Dec 2005 → … |
Conference
Conference | IJCAI International Joint Conference on Artificial Intelligence |
---|---|
Period | 1/12/05 → … |