IJAR
2010
13 years 8 months ago
2010
In the original formulation of influence diagrams (IDs), each model contained exactly one utility node. Tatman and Shachter (1990), introduced the possibility of having super-valu...
JAIR
2008
13 years 11 months ago
2008
This paper presents Networks of Influence Diagrams (NID), a compact, natural and highly expressive language for reasoning about agents' beliefs and decision-making processes....
IJAR
2006
13 years 11 months ago
2006
Although influence diagrams are powerful tools for representing and solving complex decisionmaking problems, their evaluation may require an enormous computational effort and this...
EOR
2008
13 years 11 months ago
2008
Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for representing continuous chance variables in influence diagrams. Also, MTE potentials c...
UAI
1996
14 years 9 days ago
1996
Real-time Decision algorithms are a class of incremental resource-bounded [Horvitz, 89] or anytime [Dean, 93] algorithms for evaluating influence diagrams. We present a test domai...
UAI
1994
14 years 9 days ago
1994
Most traditional models of uncertainty have focused on the associational relationship among variables as captured by conditional dependence. In order to successfully manage intell...
FLAIRS
1998
14 years 10 days ago
1998
The increasing number of knowledge-based systems that build on a Bayesian belief network or influence diagram acknowledge the usefulness of these frameworks for addressing complex...
ECAI
2006
Springer
14 years 2 months ago
2006
Springer
Abstract. In this article we present the framework of Possibilistic Influence Diagrams (PID), which allow to model in a compact form problems of sequential decision making under un...