We propose a new semantics for modeling belief, mixing conncepts from qualitative probabilistic and classical possible world accounts. Our belief structures are coherent sets of q...
This paper proposes a method of integrating two different concepts of belief in artificial intelligence: belief as a probability distribution and belief as a logical formula. The...
Probabilistic logic programming is a powerful technique to represent and reason with imprecise probabilistic knowledge. A probabilistic logic program (PLP) is a knowledge base whi...
We investigate the discrete (finite) case of the Popper-Renyi theory of conditional probability, introducing discrete conditional probabilistic models for (multi-agent) knowledge...
Modal logics based on Kripke style semantics are the prominent formalismin AI for modeling beliefs. Kripke semantics involve a collection of possible worlds and a relation among t...