Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
A valuation-based language for expert systems
International Journal of Approximate Reasoning
Readings in uncertain reasoning
Nonmonotonic reasoning, preferential models and cumulative logics
Artificial Intelligence
Objection-based causal networks
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
A general non-probabilistic theory of inductive reasoning
UAI '88 Proceedings of the Fourth Annual Conference on Uncertainty in Artificial Intelligence
Conditional plausibility measures and Bayesian networks
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Plausibility measures: a user's guide
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Action networks: a framework for reasoning about actions and change under uncertainty
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
On the relation between kappa calculus and probabilistic reasoning
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
Objection-based causal networks
UAI'92 Proceedings of the Eighth international conference on Uncertainty in artificial intelligence
Hi-index | 0.00 |
This paper demonstrates that it is possible to relax the commitment to numeric degrees of belief while retaining the desirable features of the Bayesian approach for representing and changing states of belief. We first present an abstract representation of states of belief and an associated notion of conditionalization that subsume their Bayesian counterparts. Next, we provide some symbolic and numeric instances of states of belief and their conditionalizations. Finally, we show that patterns of belief change that make Bayesianism so appealing do hold in our framework.