Towards a general theory of action and time
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
Approximating probabilistic inference in Bayesian belief networks is NP-hard
Artificial Intelligence
An evaluation of explanations of probabilistic inference
Computers and Biomedical Research - Papers presented at the 16th symposium on computer applications in medical care (SCAMC)
Representing Plans Under Uncertainty: A Logic of Time, Chance, and Action
Representing Plans Under Uncertainty: A Logic of Time, Chance, and Action
Constructing Flexible Dynamic Belief Networks from First-Order Probalistic Knowledge Bases
ECSQARU '95 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
A logic and time nets for probabilistic inference
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 1
Probabilistic temporal reasoning with endogenous change
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Learning Dynamic Bayesian Belief Networks Using Conditional Phase-Type Distributions
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Temporal Bayesian Network of Events for Diagnosis and Prediction in Dynamic Domains
Applied Intelligence
Probabilistic temporal networks: A unified framework for reasoning with time and uncertainty
International Journal of Approximate Reasoning
A temporal Bayesian network for diagnosis and prediction
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Cost-sharing in Bayesian knowledge bases
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Artificial Intelligence in Medicine
Medical informatics: reasoning methods
Artificial Intelligence in Medicine
Hi-index | 0.00 |
We developed the language of Modifiable Temporal Belief Networks (MTBNs) as a structural and temporal extension of Bayesian Belief Networks (BNs) to facilitate normative temporal and causal modeling under uncertainty. In this paper we present definitions of the model, its components, and its fundamental properties. We also discuss how to represent various types of temporal knowledge, with an emphasis on hybrid temporal-explicit time modeling, dynamic structures, avoiding causal temporal inconsistencies, and dealing with models that involve simultaneously actions (decisions) and causal and non-causal associations. We examine the relationships among BNs, Modifiable Belief Networks, and MTBNs with a single temporal granularity, and suggest areas of application suitable to each one of them.