Using hypothetical reasoning as a method for belief ascription

A key cognitive faculty that enables humans to communicate with each other is their ability to incrementally construct and use models describing the mental states of others. Every such model describing some other cognitive agent will realistically contain only a finite number of sentences in some language of thought, hence, assuming sufficiently powerful inference rules, some of its consequences will remain implicit. To make them explicit, the person holding the model could employ a kind of reasoning that can be paraphrased as 'what would I believe if I were the other person believing everything I believe that person believes', a strategy that can be viewed as a simulation of the other person's reasoning using the model of that person in conjunction with the reasoning abilities of the simulator. If we want to equip an artificial cognitive agent with such a simulative reasoning ability we have to cope with problems such as simulation at various levels of nesting, meta-reasoning to make implicit agent model information explicitly available for its use in a simulation, and the defeasibility inherent in this reasoning strategy. This paper will describe how in a propositional semantic network formalism such as SNePS, in which propositions are terms of the representation language, we can employ hypothetical reasoning to achieve an elegant solution to the problems stated above. The relevance logic-based belief revision mechanism employed by SNePS will automatically take care of some of the problems associated with the defeasibility of belief ascription by way of simulative reasoning. An example run will show how the presented solution can be used to perform simulative reasoning in the current implementation of SNePS.