Propositional knowledge base revision and minimal change
Artificial Intelligence
Qualitative probabilities: a normative framework for commonsense reasoning
Qualitative probabilities: a normative framework for commonsense reasoning
Unifying default reasoning and belief revision in a modal framework
Artificial Intelligence
Reasoning about knowledge
On the logic of iterated belief revision
Artificial Intelligence
Modeling beliefs in dynamic systems
Modeling beliefs in dynamic systems
Modeling belief in dynamic systems, part I: foundations
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
A formal model of knowledge, action, and communication in distributed systems: preliminary report
Proceedings of the fourth annual ACM symposium on Principles of distributed computing
Revisions of Knowledge Systems Using Epistemic Entrenchment
Proceedings of the 2nd Conference on Theoretical Aspects of Reasoning about Knowledge
A Critical Reexamination of Default Logic, Autoepistemic Logic, and Only Knowing
KGC '93 Proceedings of the Third Kurt Gödel Colloquium on Computational Logic and Proof Theory
On the logic of iterated belief revision
TARK '94 Proceedings of the 5th conference on Theoretical aspects of reasoning about knowledge
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
A Framework for Splitting BDI Agents
LPAR '02 Proceedings of the 9th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning
A Calculus and Complexity Bound for Minimal Conditional Logic
ICTCS '01 Proceedings of the 7th Italian Conference on Theoretical Computer Science
Filtering vs Revision and Update: Let Us Debate!
ECSQARU '95 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
Theoretical Computer Science - Logic, language, information and computation
SAICSIT '06 Proceedings of the 2006 annual research conference of the South African institute of computer scientists and information technologists on IT research in developing countries
Selecting a distributed agreement algorithm
Proceedings of the 2007 ACM symposium on Applied computing
Belief change and cryptographic protocol verification
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Admissible and restrained revision
Journal of Artificial Intelligence Research
Revision of partially ordered information: axiomatization, semantics and iteration
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Conditionals in nonmonotonic reasoning and belief revision: considering conditionals as agents
Conditionals in nonmonotonic reasoning and belief revision: considering conditionals as agents
Updating action domain descriptions
Artificial Intelligence
A change model for credibility partial order
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
Reconfigurable composition of web services using belief revision through genetic algorithm
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I
Reconfigurable web service composition using belief revision
ADCONS'11 Proceedings of the 2011 international conference on Advanced Computing, Networking and Security
Revising by an inconsistent set of formulas
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Probabilistic Belief Contraction
Minds and Machines
Hi-index | 0.00 |
We examine carefully the rationale underlying the approaches to belief change taken in the literature, and highlight what we view as methodological problems. We argue that to study belief change carefully, we must be quite explicit about the ’’ontology‘‘ or scenariounderlying the belief change process. This is something that has beenmissing in previous work, with its focus on postulates.Our analysis shows that we must pay particular attention to twoissues that have often been taken for granted: the first is how we model the agent‘s epistemic state. (Do we use a set of beliefs, or aricher structure, such as an ordering on worlds? And if we use a set ofbeliefs, in what language are these beliefs are expressed?)We show that even postulates that have been called ’’beyondcontroversy‘‘ are unreasonable when the agent‘s beliefs include beliefs about her own epistemic state as well as the external world.The second is the status ofobservations. (Are observations known to be true, or just believed? Inthe latter case, how firm is the belief?) Issues regardingthe status of observations arise particularly when we consideriterated belief revision, and we must confront the possibilityof revising by &phis; and then by ¬ &phis;.