Mental models: towards a cognitive science of language, inference, and consciousness
Mental models: towards a cognitive science of language, inference, and consciousness
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In this paper an approach to resolving semantic inconsistency of incoming messages is proposed. It is assumed that in order to collect knowledge about a current state of properties in an external object a cognitive agent asks other agents located in the same world about their knowledge of this object. The other agents reply by sending messages in which modal formulas extended with operators for knowledge, belief and possibility are conveyed. These formulas are translated by the receiving cognitive agent into related internal representations and a profile of fuzzy sets representing mental models assigned to collected formulas is developed. Due to the fact that incoming messages carry some content that can differ from one message to another the resulting collection of fuzzy sets can be inconsistent, This inconsistency means that in order to create and communicate its own prepositional attitude the cognitive agent needs to resolve the underlying semantic inconsistency. This resolution of inconsistency is achieved in two steps: the determination of a consensus for the whole profile of fuzzy sets and the choice of a formula representing the content of derived consensus. A simple method is used to derive the consensus and an adaptation of an algorithm for extracting language messages from cognitive agents is presented. This algorithm has been proposed and studied in detail in other cited works.