David Chalmers’ conceivability argument against physicalism relies on the entailment from a priori conceivability to metaphysical possibility. The a posteriori physicalist rejects this premise, but is consequently committed to psychophysical strong necessities. These don’t fit into the Kripkean model of the necessary a posteriori, and they are therefore, according to Chalmers, problematic. But ...

In this paper, we consider several types of in­ formation and methods of combination asso­ ciated with incomplete probabilistic systems. \Ve discriminate between 'a priori' and evi­ dential information. The former one is a de­ scription of the whole population, the latest is a restriction based on observations for a particular case. Then, we proposse different combination methods for each one o...

I demonstrate that a consistent interpretation of Reichenbach’s (1947) primitives and their configurations enables the construction of an intuitive and elegant semantic space for all logically possible tense meanings, independent of their mode of expression. I argue that the property which defines the perfect in absolute tense systems is the dissociation of the temporal location of the situatio...

In Conceptual Spaces (Gärdenfors 2000), dimensions and their relations provide a topological representation of a concept’s constituents and their mode of combination. Consequently, as concepts are ndimensional geometrical structures, conceptual change denotes the dynamic development of these structures. Following this basic assumption, we apply conceptual spaces to the dynamics of empirical the...

and the management of linguistically expressed uncertainty. Int.

It is suggested by Yagerr5] that default knowledge can be represented in the framework of possibility theory. In this note, we show a potential application of the proposal. That is, the priorities of defaults can be encoded into the formalism naturally and the results produced by such encoded default theories reeect the strength of the conclusions.

Possibilistic networks are important tools for modelling and reasoning, especially in the presence of imprecise and/or uncertain information. These graphical models have been successfully used in several real applications. Since their construction by experts is complex and time consuming, several researchers have tried to learn them from data. In this paper, we try to present and discuss releva...

Information is often modelled as a set of relevant possibilities, treated as logically possible worlds. However, this has the unintuitive consequence that the logical consequences of an agent’s information cannot be informative for that agent. There are many scenarios in which such consequences are clearly informative for the agent in question. Attempts to weaken the logic underlying each possi...

Qualitative possibilistic networks, also known as min-based possibilistic networks, are important tools for handling uncertain information in the possibility theory framework. Despite their importance, only the junction tree adaptation has been proposed for exact reasoning with such networks. This paper explores alternative algorithms using compilation techniques. We first propose possibilistic...

There has been an ever-increasing interest in multi-disciplinary research on representing and reasoning with imperfect data. Possibilistic networks present one of the powerful frameworks of interest for representing uncertain and imprecise information. This paper covers the problem of their parameters learning from imprecise datasets, i.e., containing multi-valued data. We propose in the first ...