Kalman filtering: theory and practice
Kalman filtering: theory and practice
A fully decentralized multi-sensor system for tracking and surveillance
International Journal of Robotics Research
Acting optimally in partially observable stochastic domains
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
On the logic of iterated belief revision
Artificial Intelligence
A unified model of qualitative belief change: a dynamical systems perspective
Artificial Intelligence
Belief revision with unreliable observations
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Journal of Logic, Language and Information
Update Postulates without Inertia
ECSQARU '95 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
Linking Transition-based Update and Base Revision
ECSQARU '95 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
Prioritized Transitions for Updates
ECSQARU '95 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
Modeling belief in dynamic systems part II: revision and update
Journal of Artificial Intelligence Research
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Dealing with uncertainty in situation assessment: towards a symbolic approach
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
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Recent extensions of classical belief change processes tend to get closer to numerical estimation techniques. A thorough investigation is proposed, in which Kalman filtering is confronted to classical AGM revision and KM update and to more recent approaches. The aim is to identify common aspects and differences, and to highlight the progressive evolution of belief change processes towards what would be a symbolic transposition of numerical estimation tools.