Extending and Automating Basic Probability Theory with Propositional Computability Logic
This work provides a new formalism for automating uncertainty reasoning, which is incremental as it builds on existing probability theory and computability logic.
The authors tackled the problem of automating uncertainty reasoning by extending classical probability theory with propositional computability logic, which is built on events/games, and they established a novel isomorphism between set operations and computability logic operations.
Classical probability theory is formulated using sets. In this paper, we extend classical probability theory with propositional computability logic. Unlike other formalisms, computability logic is built on the notion of events/games, which is central to probability theory. The probability theory based on CoL is therefore useful for {\it automating} uncertainty reasoning. We describe some basic properties of this new probability theory. We also discuss a novel isomorphism between the set operations and computability logic operations.