Logics of time and computation
Logics of time and computation
On the logic of iterated belief revision
Artificial Intelligence
Reasoning about Information Change
Journal of Logic, Language and Information
Journal of Logic, Language and Information
The logic of public announcements, common knowledge, and private suspicions
TARK '98 Proceedings of the 7th conference on Theoretical aspects of rationality and knowledge
An algorithmic approach to knowledge evolution
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Mutual enrichment through nested belief change
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Toward Reasoning about Security Protocols: A Semantic Approach
Electronic Notes in Theoretical Computer Science (ENTCS)
(Dis)Belief change based on messages processing
CLIMA IV'04 Proceedings of the 4th international conference on Computational Logic in Multi-Agent Systems
A temporal policy for trusting information
Trusting Agents for Trusting Electronic Societies
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We give a model for iterated belief change in multi-agent systems. The formal tool we use for this is a combination of modal and dynamic logic. Two core notions in our model are the expansion of the knowledge and beliefs of an agent, and the processing of new information. An expansion has been defined as the change in the knowledge and beliefs of an agent when it decides to believe an incoming formula while holding on to its current propositional beliefs. To prevent our agents from forming inconsistent beliefs they do not expand with every piece of information they receive. Instead, our agents remember their original beliefs and every piece of information they receive. After every receipt of information they decide which (consistent) subset of the received information should be incorporated into their original beliefs. This procedure is called the processing of new information. We show that our model of belief update behaves in an intuitive way and that it is not sensitive to criticism on comparable models.