Aleatoric Dynamic Epistemic Logic for Learning Agents

摘要

We propose a generalisation of dynamic epistemic logic, where propositions are aleatoric: that is, rather than having true/false values, propositions have odds of being true. Agents in such a system suppose a probability distribution of possible worlds, and based on observations are able to refine this probability distribution to match their observations. We demonstrate this logic with respect to some games of chance.