| Concept map assessment for teaching computer programming J Keppens, D Hay Computer Science Education 18 (1), 31-42, 2008 | 84 | 2008 |
| Knowledge based crime scenario modelling J Keppens, B Schafer Expert Systems with Applications 30 (2), 203-222, 2006 | 81 | 2006 |
| On compositional modelling J Keppens, Q Shen The knowledge engineering review 16 (2), 157-200, 2001 | 66 | 2001 |
| A scenario-driven decision support system for serious crime investigation Q Shen, J Keppens, C Aitken, B Schafer, M Lee Law, Probability and Risk 5 (2), 87-117, 2006 | 56 | 2006 |
| A model based reasoning approach for generating plausible crime scenarios from evidence J Keppens, J Zeleznikow Proceedings of the 9th international conference on artificial intelligence …, 2003 | 50 | 2003 |
| Linguistic bayesian networks for reasoning with subjective probabilities in forensic statistics J Halliwell, J Keppens, Q Shen Proceedings of the 9th international conference on artificial intelligence …, 2003 | 45 | 2003 |
| Argument diagram extraction from evidential Bayesian networks J Keppens Artificial Intelligence and Law 20, 109-143, 2012 | 41 | 2012 |
| Impact of receiving recorded mental health recovery narratives on quality of life in people experiencing psychosis, people experiencing other mental health problems and for … S Rennick-Egglestone, R Elliott, M Smuk, C Robinson, S Bailey, R Smith, ... Trials 21 (1), 1-34, 2020 | 28 | 2020 |
| Efficient norm emergence through experiential dynamic punishment S Mahmoud, N Griffiths, J Keppens, M Luck ECAI 2012, 576-581, 2012 | 28 | 2012 |
| Towards qualitative approaches to Bayesian evidential reasoning J Keppens Proceedings of the 11th international conference on artificial intelligence …, 2007 | 27 | 2007 |
| On extracting arguments from Bayesian network representations of evidential reasoning J Keppens Proceedings of the 13th international conference on artificial intelligence …, 2011 | 25 | 2011 |
| DESO: Addressing volume and variety in large-scale criminal cases O Brady, R Overill, J Keppens Digital Investigation 15, 72-82, 2015 | 24 | 2015 |
| Compositional Bayesian modelling for computation of evidence collection strategies J Keppens, Q Shen, C Price Applied Intelligence 35, 134-161, 2011 | 23 | 2011 |
| Probabilistic abductive computation of evidence collection strategies in crime investigation J Keppens, Q Shen, B Schafer Proceedings of the 10th international conference on artificial intelligence …, 2005 | 23 | 2005 |
| Children's Rights: Monitoring Issues. E Verhellen, F Spiesschaert Mys & Breesch, Coupure 120-B-9000, Gent, Belgium (950 Belgian Francs)., 1994 | 23 | 1994 |
| An analysis of norm emergence in axelrod's model S Mahmoud, N Griffiths, J Keppens, M Luck | 21 | 2010 |
| Establishing norms with metanorms in distributed computational systems S Mahmoud, N Griffiths, J Keppens, A Taweel, TJM Bench-Capon, M Luck Artificial Intelligence and Law 23, 367-407, 2015 | 19 | 2015 |
| On the role of model-based reasoning in decision support in crime investigation J Keppens, J Zeleznikow Proceedings of the 3rd International Conference on Law and Technology, 77-83, 2002 | 19 | 2002 |
| Requirements analysis: Evaluating kaos models F Almisned, J Keppens Journal of Software Engineering and Applications 3 (9), 869, 2010 | 18 | 2010 |
| Compositional model repositories via dynamic constraint satisfaction with order-of-magnitude preferences J Keppens, Q Shen Journal of Artificial Intelligence Research 21, 499-550, 2004 | 18 | 2004 |
Michael LuckDepartment of Informatics, King's College LondonDirección de correo verificada de kcl.ac.uk
