A model for reasoning about persistence and causation
Computational Intelligence
Planning and control
A computational scheme for reasoning in dynamic probabilistic networks
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
Using Mutual Information to Determine Relevance in Bayesian Networks
PRICAI '98 Proceedings of the 5th Pacific Rim International Conference on Artificial Intelligence: Topics in Artificial Intelligence
A Mathematical Theory of Communication
A Mathematical Theory of Communication
The BATmobile: towards a Bayesian automated taxi
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Tractable inference for complex stochastic processes
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Stochastic simulation algorithms for dynamic probabilistic networks
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Review: learning bayesian networks: Approaches and issues
The Knowledge Engineering Review
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Dynamic Belief Networks (DBNs) have become a popular method for monitoring dynamical processes in real-time. However DBN evaluation has the same problems of computationeJ intractability as ordinary belief networks, with additional exponential complexity as the number of time-slices increases. Several approximate methods for fast DBN evaluation have been devised [1,3,11]. We present a new method which simplifies evaluation by selectively "forgetting" past events and their relationships to the present. This is done by pruning, from past time-slices, arcs and nodes which are deemed less relevant to the current time-slice, as determined by the arc weight measure introduced in [15]. This approach is more flexible than a fixed-size window and can be combined with other approximate evaluation techniques.