Assumption Based Peg Unification for Crime Scenario Modelling

Burkhard Schafer, Jeroen Keppens

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

An important cause of miscarriages of justice is the failure of crime investigators and lawyers to consider important plausible explanation for the available evidence. Recent research has explored the development of decision support systems that (i) assist human crime investigators by proposing plausible crime scenarios explaining given evidence, and (ii) provide the means to analyse such scenarios. While such approaches can generate useful explanations, they are inevitably restricted by the limitations of formal abductive inference mechanisms. Building on work presented previously at this venue, this paper characterises an important class of scenarios, containing 'alternative suspects' or 'hidden objects', which cannot be synthesised robustly using conventional abductive inference mechanisms. The work is then extended further by proposing a novel inference mechanism that enables the generation of such scenarios.
Original languageEnglish
Title of host publicationLegal Knowledge and Information Systems - JURIX 2005
Subtitle of host publicationThe Eighteenth Annual Conference on Legal Knowledge and Information Systems, Brussels, Belgium, 8-10 December 2005
EditorsMarie-Francine Moens, Peter Spyns
PublisherIOS Press
Pages49-58
ISBN (Print)9781586035761
Publication statusPublished - 2005

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume134

Fingerprint

Dive into the research topics of 'Assumption Based Peg Unification for Crime Scenario Modelling'. Together they form a unique fingerprint.

Cite this