Multiagent Reasoning with Belief Contexts II: Elaboration Tolerance

have shown how the modularity of belief contexts provides elaboration tolerance. First, we have shown how reasoning about mutual and nested beliefs, common belief, ignorance and ignorance ascription, can be formalized using belief contexts in a very general and structured way. Then we have shown how several variations to the OTWM are formalized simply by means of \local" variations to the OTWM solution given in (Cimatti & Seraani 1995a). Despite its relevance, elaboration tolerance has been of relatively little interest in the past; often representation formalisms are compared only on the basis of their expressive power, rather than their tolerance to variations. As a result, very few have tried to address this problem seriously. The work by Konolige might be thought of as an exception: in (Konolige 1984) a for-malization of the not so wise man puzzle is presented, while in (Konolige 1990) (a simpliied version of) the scenario described in section is formalized. However, his motivations seem diierent than showing the elaboration tolerance of the formalism. A more detailed comparison of our approach with other formalisms for multiagent reasoning is given in (Cimatti & Seraani 1995a). Our work on belief context has mainly addressed formal issues. We have mechanized in GETFOL, (an interactive system for the mechanization of multicontext system (Giunchiglia 1992)) the systems of contexts and the formal proofs (this work is described in (Cimatti & Seraani 1995b)). However, this is formal reasoning about the puzzle. It is only a part (though an important one) of what is needed for building situated systems using belief contexts as reasoning tools, which is our long term goal. The next step is to build systems playing the wise men, adding to the reasoning ability the following features. First, these systems should have some sensing (e.g., seeing, listening) and some acting (e.g. speaking) capabilities, in order to perceive and aaect the environment they are situated into; furthermore, they should be able to decide what actions to perform. Finally, they should be able to build the appropriate formal system to reason about the scenarios on the basis of the data perceived by the sensors: other agents' spots should be looked at to devise a State-of-aaairs axiom, \unusual" features of the wise men (e.g. being not so wise, or blind) might be told by the king, and also the number of wise men should not be known a priori.