Abstract

This paper is concerned with the implementation of Prediction Theories. Rather than developing and then attempting to implement a proof theory, it aims instead to implement their model theory by building computational counterparts of their relevant models. Prediction Theories are outlined and examples involving inertia, qualifications, ramifications and concurrency are given. The basic model-building algorithm is then presented and its completeness and correctness is proved. Several extensions to this algorithm are then outlined. Finally, the performance of the algorithms is analysed. 1 Introduction This paper is concerned with the implementation of Prediction Theories (PTs) (Bell, 1997). PTs were developed to represent predictive common sense causal reasoning. In particular they provide a modeltheoretic means of representing inertia, ramifications, qualifications, simultaneity, and non-determinism. Rather than developing and then attempting to implement a proof theory f...

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