Artificial Intelligence
Higher order probability and intervals
International Journal of Approximate Reasoning
Two views of belief: belief as generalized probability and belief as evidence
Artificial Intelligence
Abstract probabilistic modeling of action
Proceedings of the first international conference on Artificial intelligence planning systems
Artificial Intelligence
Probability Intervals Over Influence Diagrams
IEEE Transactions on Pattern Analysis and Machine Intelligence
Propagation of Uncertainty in Dependence Graphs
ECSQAU Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
Independence concepts for convex sets of probabilities
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Propagation of 2-monotone lower probabilities on an undirected graph
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Irrelevance and Independence Axioms in Quasi-Bayesian Theory
ECSQARU '95 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
Partially observable Markov decision processes with imprecise parameters
Artificial Intelligence
Separation properties of sets of probability measures
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Irrelevance and independence relations in Quasi-Bayesian networks
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Robustness analysis of Bayesian networks with local convex sets of distributions
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Propagation of 2-monotone lower probabilities on an undirected graph
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Atanassov's intuitionistic fuzzy probability and Markov chains
Knowledge-Based Systems
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It is shown that the ability of the interval probability representation to capture epistemological independence is severely limited. Two events are epistemologically independent if knowledge of the first event does not alter belief (i.e., probability bounds) about the second. However, iudependence in this form can only exist in a 2-monotone probability function in degenerate cases -- i.e., if the prior bounds are either point probabilities or entirely vacuous. Additional limitations are characterized for other classes of lower probabilities as well. It is argued that these phenomena are a matter of interpretation. They appear to be limitations when one interprets probability bounds as a measure of epistemological indeterminacy (i.e., uncertainty arising from a lack of knowledge), but are exactly as one would expect when probability intervals are interpreted as representations of ontological indeterminacy (indeterminacy introduced by structural approximations).