Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
gIBIS: a hypertext tool for exploratory policy discussion
ACM Transactions on Information Systems (TOIS)
Explanation and prediction: an architecture for default and abductive reasoning
Computational Intelligence
Readings in model-based diagnosis
Readings in model-based diagnosis
Progress on Room 5: a testbed for public interactive semi-formal legal argumentation
Proceedings of the 6th international conference on Artificial intelligence and law
Robust model-based fault diagnosis for dynamic systems
Robust model-based fault diagnosis for dynamic systems
Automated argument assistance for lawyers
ICAIL '99 Proceedings of the 7th international conference on Artificial intelligence and law
Probability updating using second order probabilities and conditional event algebra
Information Sciences: an International Journal
Principles of data mining
Machine Learning
Context-specific sign-propagation in qualitative probabilistic networks
Artificial Intelligence
Multiple Regression Analysis in Crime Pattern Warehouse for Decision Support
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
Qualitative probability and order of magnitude reasoning
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Argumentation schemes and generalisations in reasoning about evidence
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
Linguistic Bayesian Networks for reasoning with subjective probabilities in forensic statistics
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
A model based reasoning approach for generating plausible crime scenarios from evidence
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
Probabilistic abductive computation of evidence collection strategies in crime investigation
ICAIL '05 Proceedings of the 10th international conference on Artificial intelligence and law
Human-Computer Interaction (3rd Edition)
Human-Computer Interaction (3rd Edition)
Artificial Intelligence and Law
Towards qualitative approaches to Bayesian evidential reasoning
Proceedings of the 11th international conference on Artificial intelligence and law
Argument diagramming in logic, law and artificial intelligence
The Knowledge Engineering Review
Linguistic probabilities: theory and application
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue on Uncertainty Analysis and Decision Making; Guest Editors: Yan-Kui Liu, Baoding Liu, Jinwu Gao
Model Driven Engineering and Ontology Development
Model Driven Engineering and Ontology Development
Journal of Artificial Intelligence Research
Visualizing criminal relationships: comparison of a hyperbolic tree and a hierarchical list
Decision Support Systems
Knowledge based crime scenario modelling
Expert Systems with Applications: An International Journal
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
Efficient reasoning in qualitative probabilistic networks
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Refining reasoning in qualitative probabilistic networks
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Suspect vehicle identification for border safety with modified mutual information
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
On extracting arguments from Bayesian network representations of evidential reasoning
Proceedings of the 13th International Conference on Artificial Intelligence and Law
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As forensic science and forensic statistics become increasingly sophisticated, and judges and juries demand more timely delivery of more convincing scientific evidence, crime investigation is becoming progressively more challenging. In particular, this development requires more effective and efficient evidence collection strategies, which are likely to produce the most conclusive information with limited available resources. Evidence collection is a difficult task, however, because it necessitates consideration of: a wide range of plausible crime scenarios, the evidence that may be produced under these hypothetical scenarios, and the investigative techniques that can recover and interpret the plausible pieces of evidence. A knowledge based system (KBS) can help crime investigators by retrieving and reasoning with such knowledge, provided that the KBS is sufficiently versatile to infer and analyse a wide range of plausible scenarios. This paper presents such a KBS. It employs a novel compositional modelling technique that is integrated into a Bayesian model based diagnostic system. These theoretical developments are illustrated by a realistic example of serious crime investigation.