We present a framework for incorporating perception-induced beliefs into the knowledge base of a rational agent. Normally, the agent accepts the propositional content of perception...
Belief revision always results in trusting new evidence, so it may admit an unreliable one and discard a more confident one. We therefore use belief change instead of belief revis...
Intelligent agents require methods to revise their epistemic state as they acquire new information. Jeffrey’s rule, which extends conditioning to probabilistic inputs, is appropr...
Salem Benferhat, Didier Dubois, Henri Prade, Mary-...
Abstract. We introduce a nonmonotonic framework for belief revision in which reasoning about the reliability of different pieces of information based on meta-knowledge about the in...
ABSTRACT. We show how belief revision can be treated systematically in the format of dynamicepistemic logic, when operators of conditional belief are added. The core engine consist...
The capability of revising its beliefs upon new information in a rational and efficient way is crucial for an intelligent agent. The classical work in belief revision focuses on i...
We look at the problem in belief revision of trying to make inferences about what an agent believed--or will believe--at a given moment, based on an observation of how the agent h...
This position paper discusses the difficulty of interpreting iterated belief revision in the scope of the existing literature. Axioms of iterated belief revision are often present...
In this paper, we present a semantical approach to multi-agent belief revision and belief update. For this, we introduce relational structures called conditional doxastic models (...
We refine our algebraic axiomatization in [8,9] of epistemic actions and epistemic update (notions defined in [5,6] using Kripke-style semantics), to incorporate a mechanism for d...