ABSTRACT
We present a simple metrical representation and algorithm to explain putative imagery processes underlying the empirical mental model preferences found by Knauff, Rauh and Schlieder (1995) for Allen inferences (Allen, 1983). The computational theory is compared with one based on ordinal information only (Schlieder, in preparation). Both provide good fits with the data. They differ psychologically in background theories, visualisation strategies motivated by these, and model construction processes generating models with the properties indicated as desirable by the strategies. They differ computationally in assumptions about knowledge strength (ordinal: weaker) and algorithmic simplicity (metrical: simpler). Our theory and its comparison with the ordinal theory provide the basis for a discussion of issues pertaining to imagery in general: Using the assumption of imagery inexactness, we develop a sketch theory of mental images and motivate a new visualisation strategy ('regularisation'). We demonstrate systematic methods of modelling imagery processes and of analysing such models. We also outline some criteria for comparison (and future integration?) of cognitive modelling approaches.
