Belief Revision as Applied within a Descriptive Model of Jury Deliberations

Aldo Franco Dragoni, Paolo Giorgini, Ephraim Nissan
2001 Information & communications technology law  
Belief revision is a well-research topic within AI. We argue that the new model of belief revision as discussed here is suitable for general modelling of judicial decision making, along with extant approach as known from jury research. The new approach to belief revision is of general interest, whenever attitudes to information are to be simulated within a multi-agent environment with agents holding local beliefs yet by interacting with, and influencing, other agents who are deliberating
more » ... deliberating collectively. The principle of "priority to the incoming information", as known from AI models of belief revision, is problematic when applied to factfinding by a jury. The present approach incorporates a computable model for local belief revision, such that a principle of recoverability is adopted. By this principle, any previously held belief must belong to the current cognitive state if consistent with it. For the purposes of jury simulation such a model calls for refinement. Yet, we claim, it constitutes a valid basis for an open system where other AI functionalities (or outer stimuli) could attempt to handle other aspects of the deliberation which are more specific to legal narratives, to argumentation in court, and then to the debate among the jurors.
doi:10.1080/13600830123621 fatcat:wnuuxjok2jds3kovvufxf22y4i