Worlds as a Unifying Element of Knowledge Representation

Abstract Computational systems with the abilities of human biological intelligence must be able to reason about the beliefs of others, hypothetical and future situations, quantifiers, probabilities, and counterfactuals. While each of these deals in some way with reasoning about alternative states of reality, no single knowledge representation framework deals with them in a unified and scalable manner. As a consequence it is difficult to build cognitive systems for domains that require each of these abilities to be used together. To enable this integration we propose a representational framework based on synchronizing beliefs between worlds. This framework is consistent with evidence that performing mental simulations of the world is a ubiquitous aspect of human intelligence. Using this framework, each of these tasks can be reformulated into a reasoning problem involving worlds. This demonstrates that the notions of worlds and inheritance can bring significant parsimony and broad new abilities to knowledge representation.

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