A Dynamic Epistemic Logic for Resource-Bounded Agents

In this paper, we present a dynamic epistemic logic suitable for resource-bounded agents. Our setting is informed by empirical evidence on deductive reasoning performance and therefore it avoids the problem of logical omniscience. In particular, we introduce actions capturing how the agent learns, forgets, and applies inference rules. Our model is a variant of Kripke models extended with impossible worlds and our updates modify its components (epistemic accessibility, rule availability, cognitive capacity) according to each action's effect. We further provide a sound and complete axiomatization, through a method connecting this semantic approach to logical omniscience with more syntactically-oriented ones. Finally, we use similar tools to model moderate introspective ability and thus avoid the unrealistic commitment to unbounded introspection.