Bayesian and non-Bayesian evidential updating
Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in expert systems: theory and algorithms
Probabilistic reasoning in expert systems: theory and algorithms
A sufficiently fast algorithm for finding close to optimal clique trees
Artificial Intelligence
Introduction to Bayesian Networks
Introduction to Bayesian Networks
Local computation with valuations from a commutative semigroup
Annals of Mathematics and Artificial Intelligence
A Differential Approach to Inference in Bayesian Networks
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Justifying Multiply Sectioned Bayesian Networks
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
Agent-encapsulated bayesian networks
Agent-encapsulated bayesian networks
Time-critical decision making with communicating influence diagrams
Time-critical decision making with communicating influence diagrams
Probability update: conditioning vs. cross-entropy
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
An approach to hybrid probabilistic models
International Journal of Approximate Reasoning
Performance Evaluation of Algorithms for Soft Evidential Update in Bayesian Networks: First Results
SUM '08 Proceedings of the 2nd international conference on Scalable Uncertainty Management
Agent-encapsulated Bayesian networks and the rumor problem
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
On the combination of logical and probabilistic models for information analysis
Applied Intelligence
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Autonomous agents that communicate using probabilistic information and use Bayesian networks for knowledge representation need an update mechanism that goes beyond conditioning on the basis of evidence. In a related paper (M. Valtorta, Y.G. Kim, and J. Vomlel, International Journal of Approximate Reasoning, vol. 29, no. 1, pp. 71–106, 2002), we describe this mechanism, which we call soft evidential update, its properties, and algorithms to realize it. Here, we describe an implementation of the most promising such algorithm, the big clique algorithm, together with examples of its use.