Logic, Reasoning under Uncertainty and Causality

Abstract

A simple framework for reasoning under uncertainty and intervention is introduced. This is achieved in three steps. First, logic is restated in set-theoretic terms to obtain a framework for reasoning under certainty. Second, this framework is extended to model reasoning under uncertainty. Finally, causal spaces are introduced and shown how they provide enough information to model knowledge containing causal information about the world.