Dark Matter of Epistemology
The CUNY Graduate Center
We have already shown that only deductively complete epistemic scenarios admit traditional single-model characterizations. In this talk we show that the paradigmatic Muddy Children story is deductively complete and fairly represented by its standard Kripke model. However, the whole variety of its modifications with partial knowledge, asymmetric knowledge, etc., are not deductively complete and hence are invisible “Dark Matter” from the traditional single-model perspective. We show several examples of such “invisible” scenarios that admit natural syntactic analysis and resolution. Finally, we will discuss a version of Muddy Children, in which justifications become a key ingredient of the solution. These examples represent, in a nutshell, the corresponding classes of real world epistemic problems which lie off limits of the traditional single-model analysis but can be analyzed by a proper combination of syntactic and semantic methods.
Professor Artemov holds a Distinguished Professor position at the Graduate Center of the City University of New York, in the Computer Science, Mathematics and Philosophy programs. He is also Professor of Mathematics at Moscow State University, the founder and the Head of the research laboratory Logical Problems in Computer Science. He conducts research in the areas of logic in computer science, mathematical logic and proof theory, knowledge representation and artificial intelligence, automated deduction and verification and optimal control and hybrid systems.