image and the role of elaboration tolerance in solving the qualification problem Original Research Article

We describe image (image), a specialized, model-theoretic logic for reasoning about actions. image is able to represent non-deterministic domains involving concurrency, static laws (constraints), indirect effects (ramifications), and narrative information in the form of action occurrences and observations along a time line. We give formal results which characterize imageʹs high degree of modularity and elaboration tolerance, and show how these properties help to separate out, and provide principled solutions to, different aspects of the qualification problem. In particular, we identify the endogenous qualification problem as the problem of properly accounting for highly distributed, and potentially conflicting, causal knowledge when reasoning about the effects of actions. We show how a comprehensive solution to the endogenous qualification problem helps simplify the exogenous qualification problem — the problem of reconciling conflicts between predictions about what should be true at particular times and actual observations. More precisely, we describe how image is able to use straightforward default reasoning techniques to solve the exogenous qualification problem largely because its robust treatments of the frame, ramification and endogenous qualification problems combine into a particular characteristic of elaboration tolerance that we formally encapsulate as a notion of “free will”.