Paul D. Thorn

Agents typically revise their beliefs when confronted with evidence that contradicts those beliefs, selecting from a number of possible revisions sufficient to reestablish consistency. In cases where an individual’s beliefs concern spatial relations, belief revision has been fruitfully treated as a decision about which features of an initially constructed spatial mental model to modify. A normative claim about belief revision maintains that agents should prefer minimal belief revisions. Yet recent studies have rebutted the preceding claim, where minimality is understood to consist in modifying the position of the fewest objects, showing instead that reasoners prefer revisions that modify the position of an object x while retaining the position of an object y, when the agent’s new evidence is a relational statement of the form ‘xRy’. We here present cases where the preceding effect is reduced, and show an effect of minimality as measured by the number of initial premises preserved.

Systems of logico-probabilistic reasoning characterize inference from conditional assertions that express high conditional probabilities. In this paper we investigate four prominent LP systems, the systems _O, P_, _Z_, and _QC_. These systems differ in the number of inferences they licence _. LP systems that license more inferences enjoy the possible reward of deriving more true and informative conclusions, but with this possible reward comes the risk of drawing more false or uninformative conclusions. In the first part of the paper, we present the four systems and extend each of them by theorems that allow one to compute almost-tight lower-probability-bounds for the conclusion of an inference, given lower-probability-bounds for its premises. In the second part of the paper, we investigate by means of computer simulations which of the four systems provides the best balance of reward versus risk. Our results suggest that system _Z_ offers the best balance.