Skip to main content
SpringerLink
Log in
Book cover

International Symposium on Methodologies for Intelligent Systems

ISMIS 1997: Foundations of Intelligent Systems pp 328–337Cite as

Towards AI formalisms for legal evidence

  • Communications Session 4A Knowledge Representation & Methodologies
  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1325))

This is a preview of subscription content, log in via an institution.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Allen, J.F. 1983. “Recognizing Intentions from Natural Language Utterances”. In M. Bradie and R.C. Berwick (ed), Computational Models of Discourse. MIT Press.

    Google Scholar 

  2. Allen, R.J. 1997. “Rationality, algorithms and juridical proof: a preliminary inquiry”. Lead article, special issue, Int. J. of Evidence and Proof.

    Google Scholar 

  3. Asher, N. and Sablayrolles, P. 1995. “A typology and discourse semantics for motion verbs and spatial PPs in French”. Journal of Semantics 12(2): 163–209.

    Google Scholar 

  4. Barrett, K.C., Zahn-Waxler, C. and Cole, P.M. 1993. “Avoiders vs. amenders: implications for the investigation of guilt and shame during toddlerhood?”. Cognition & Emotion 7(6): 481–506.

    Google Scholar 

  5. Bennun, M.E. 1996. “Computerizing criminal law: problems of evidence, liability and mens rea”. Information & Communications Technology Law 5(1): 29–44.

    Google Scholar 

  6. Brown, M.A. and Carmo, J. (eds) 1996. Deontic Logic, Agency and Normative Systems. Berlin: Springer-Verlag.

    Google Scholar 

  7. Berman, D.H., Hafner, C.D. and Sartor, G. (eds) 1992-Artificial Intelligence and Law (journal). Dordrecht: Kluwer.

    Google Scholar 

  8. Bohan, T.L. 1991. “Computer-aided accident reconstruction: its role in court”. SAE Technical Paper Series (12 p.).

    Google Scholar 

  9. Caldwell, C., V.S. Johnston 1989. “Tracking a criminal suspect through ‘face-space’ with a genetic algorithm”. Proc. 3rd Int. Conf. Genetic Algorithms, 416–421.

    Google Scholar 

  10. Cohn, A.G., Gooday, J.M. and Bennett, B. 1994. “A comparison of structures in spatial and temporal logics”. In R. Casati and G. White (eds), Philosophy in the Cognitive Sciences. Vienna: Hö1der-Pichler-Tempsky.

    Google Scholar 

  11. Dyer, M.G. 1983. In-Depth Understanding: A Computer Model of Integrated Processing of Narrative Comprehension. Cambridge, MA: The MIT Press.

    Google Scholar 

  12. Edwards, D. and Potter, J. 1995. “Attribution”. Ch. 4 in R. Harré and P. Stearns (eds), Discursive Psychology in Practice. London: SAGE, 87–119.

    Google Scholar 

  13. Fakher-Eldeen, F., Kuflik, Ts., Nissan, E., Puni, G., Salfati, R., Shaul, Y. and Spanioli, A. 1993. “Interpretation of imputed behavior in ALIBI (1 to 3) and SKILL”. Informatica e Diritto, Year XIX, 2nd Series, Vol. II, No. 1/2: 213–242.

    Google Scholar 

  14. Fikes, R.E. and Nilsson, N.J. 1971. “STRIPS: A new approach to the application of theorem proving to problem solving”. Artificial Intelligence 2: 89–205.

    Google Scholar 

  15. Freeman, K. and Farley, A.M. 1996. “A model of argumentation and its application to legal reasoning”. Artificial Intelligence and Law 4(34): 157–161.

    Google Scholar 

  16. Fricker, E. 1987. “The epistemology of testimony”. Aristotelian Society Supplementary Volume 61: 57–83.

    Google Scholar 

  17. Gaines, D.M., Brown, D.C. and Doyle, J.K. 1996. “A computer simulation model of juror decision making”. Expert Systems With Applications 11(1): 13–28.

    Google Scholar 

  18. Gardner, A. v.d.L. 1987. An Artificial Intelligence Approach to Legal Reasoning. Cambridge, MA: The MIT Press.

    Google Scholar 

  19. Grosz, B., Kraus, S. 1996. “Collaborative plans for complex group action”. AIJ 86.

    Google Scholar 

  20. Hastie, R. (ed) 1993. Inside the Juror: The Psychology of Juror Decision Making. Cambridge, U.K.: Cambridge University Press.

    Google Scholar 

  21. Hastie, R., Penrod, S.D. and Pennington,N. 1993. Inside the Jury. Cambridge, MA: Harvard University Press.

    Google Scholar 

  22. Hayes-Roth B. and van Gent, R. 1996. “Story-making with improvisational puppets and actors”. Tech. Rep. KSL-96-05, Knowl. Sys. Lab., Stanford.

    Google Scholar 

  23. Holmström-Hintikka, G. 1995. “Expert witnesses in legal argumentation”. Argumentation 9(3): 489–502.

    Google Scholar 

  24. Holt, A.W., Meldman, J.A. 1971. “Petri nets and legal systems”. Jurimetrics 12(2).

    Google Scholar 

  25. Holyoak, K.J. and Cheng, P.W. 1995. “Pragmatic reasoning from multiple points of view: a response”. Thinking & Reasoning 1(4): 373–389.

    Google Scholar 

  26. Jackson, B.S. 1996. “'Anchored narratives’ and the interface of law, psychology and semiotics”. Legal and Criminological Psychology 1(1): 17–45.

    Google Scholar 

  27. Jameson, A. 1983. “Impression monitoring in evaluation-oriented dialog: the role of the listener's assumed expectations and values in the generation o informative statements”. Proc. 8th IJCAI, Karlsruhe, Vol. 2, pp. 616–620.

    Google Scholar 

  28. Jones, A.J.I. and Sergot, M. 1992. “Deontic logic in the representation of law: towards a methodology”. Artificial Intelligence and Law 1(1): 45–64.

    Google Scholar 

  29. Keane, A. 1994. The Modern Law of Evidence, 3rd edn. London: Butterworth.

    Google Scholar 

  30. Kowalski, R.A., Toni, F. 1996 “Abstract argumentation” AI&Law 4(34):275–296.

    Google Scholar 

  31. Kraus, S. 1996. “An overview of incentive contracting”. AIJ 83(2): 297–346.

    Google Scholar 

  32. Kuflik, Ts., Nissan, E. and Puni, G. 1991. “Finding excuses with ALIBI: alternative plans that are deontically more defensible”. Computers and Artificial Intelligence 10(4): 297–325 (1991). Also in J. Lopes Alves (ed), Information Technology & Society: Theory, Uses, Impacts. Lisbon: Associação Portuguesa para o Desenvolvimento das Comunicações, & Sociedade Portuguesa de Filosofia: 484–510 (1992).

    Google Scholar 

  33. Linde, C. 1993. Life Stories: The Creation of Coherence. New York: Oxford UP.

    Google Scholar 

  34. Loui, R.P. and Norman, J. 1995. “Rationales and Argument Moves” Artificial Intelligence and Law 3(3): 159–190.

    Google Scholar 

  35. MacCrimmon, M.T. 1989. “Facts, stories and the hearsay rule”. In A.A. Martino (ed), Logica, Informatica, Diritto: Legal Expert Systems (Pre-proceedings of the Third International Conference,. 2 vols. + Appendix). Florence: Istituto per la Documentazione Giuridica, Vol. 1, pp. 461–475.

    Google Scholar 

  36. Martino, A.A. 1994. “Artificial intelligence and law”. International Journal of Law and Information Technology 2(2): 154–193.

    Google Scholar 

  37. Martino, A.A. and Nissan, E. (eds) 1997. Models of Time, Action, and Situations. Special issue in preparation for Artificial Intelligence and Law.

    Google Scholar 

  38. Martino, A.A. and Nissan, E. (eds) 1997. Formal Approaches to Legal Evidence. Part 1: Probabilistic Models. Part 2: Belief & Agency, Relevancy, and Argumentation. Special issue in preparation for Artificial Intelligence and Law.

    Google Scholar 

  39. May, R. 1995. “Criminal practice”. In Criminal Evidence, 3rd edn. London: Sweet & Maxwell.

    Google Scholar 

  40. McDowell, J. 1994. “Knowledge by hearsay”. In B.K. Matilal and A. Chakrabarti (eds), Knowing from Words. Dordrecht: Kluwer.

    Google Scholar 

  41. Meldman, J.A. 1975. “A preliminary study in computer-aided legal analysis”. Dissertation. Technical Report MAC-TR-157. Cambridge, MA: MIT.

    Google Scholar 

  42. Moulin, B. and Rousseau, D. 1994. “A multi-agent approach for modelling conversations”. In Proceedings of the International Avignon Conference AI 94, Natural Language Processing Sub-Conference, Paris, France, June 1994, pp. 35–50.

    Google Scholar 

  43. Nicoloff, F. 1989. “Threats and illocutions”. Journal of Pragmatics 13(4): 501–522.

    Google Scholar 

  44. Nissan, E. 1995. “SEPPHORIS: an augmented hypergraph-grammar representation for events, stipulations, and legal prescriptions”. Law, Computers, and Artificial Intelligence 4(1): 33–77.

    Google Scholar 

  45. Nissan, E. 1995. “Meanings, expression, and prototypes”. Pragmatics and Cognition 3(2): 317–364.

    Google Scholar 

  46. Nissan, E. 1996. “From ALIBI to COLUMBUS: the long march to self-aware computational models of humor”. In J. Hulstijn and A. Nijholt (eds), Automatic Interpretation and Generation of Verbal Humor. Univ. Twente, pp. 69–85.

    Google Scholar 

  47. Nissan, E. (in press). “Notions of place” (2 parts, 104 p.). In A.A. Martino (ed), Norms: Logic & Computation. In Memoriam Carlos E. Alchourrón. Pisa: SEU.

    Google Scholar 

  48. Nissan, E. and Shimony, S.E. 1997. “VEGEDOG: formalism, vegetarian dogs, and partonomies in transition”. Computers and Artificial Intelligence 16(1): 79–104.

    Google Scholar 

  49. Parry, A. 1991. “A universe of stories”. Family Process 30(1): 37–54.

    Google Scholar 

  50. Poulin, D., Mackaay, E., Bratley, P., Frémont, J. 1992. “Time Server: a legal time specialist”. In A. Martino (ed), Expert Systems in Law. North-Holland, 295–312.

    Google Scholar 

  51. Prakken, H. and Sartor, G. 1996. “A dialectical model of assessing conflicting arguments in legal reasoning”. Artificial Intelligence and Law 4(3/4): 331–368.

    Google Scholar 

  52. Prakken, H. and Sergot, M.J. 1996.“Contrary-to-duty obligations”. Studia Logica 57: 91–115.

    Google Scholar 

  53. Prakken, H. and Sergot, M.J. 1996. “Dyadic deontic logic and contrary-to-duty obligations”. In D.N. Nute (ed), Defeasible Deontic Logic: Essays in Nonmonotonic Normative Reasoning. (Synthese Library.) Dordrecht: Kluwer.

    Google Scholar 

  54. Rissland, E.L., Skalak, D.B. and Friedman, M.T. 1996. “BankXX: supporting legal arguments through heuristic retrieval”. Artificial Intelligence and Law 4(1): 1–71.

    Google Scholar 

  55. Robertson, B. and Vignaux, G.A. 1995. Interpreting Evidence: Evaluating Forensic Science in the Courtroom. Chichester, West Sussex: Wiley.

    Google Scholar 

  56. Rousseau, D. 1995. “Modelisation et simulation de conversations dans un univers multi-agent”. Ph.D. Dissertation. Technical Report 993, Department of Computer Science and Operational Research, University of Montreal.

    Google Scholar 

  57. Rousseau, D. 1996. “Personality in synthetic agents”. Technical Report KSL-96-21, Knowledge Systems Laboratory, Stanford University.

    Google Scholar 

  58. Rousseau, D., Moulin, B. and Lapalme, G. 1997. “Interpreting communicative acts and building a conversational model”. Journal of Natural Language Engineering.

    Google Scholar 

  59. Sappington, D. 1984. “Incentive contracting with asymmetric and imperfect precontractual knowledge”. Journal of Economic Theory 34: 52–70.

    Google Scholar 

  60. Schum, D. 1993. “Argument structuring and evidence evaluation”. [20]: 175–191.

    Google Scholar 

  61. Schum, D. and Tillers, P. 1991. “Marshalling evidence for adversary litigation”. Cardozo Law Review 13(2/3): 657–704.

    Google Scholar 

  62. Skalak, D.B. and Rissland, E.L. 1992. “Arguments and cases: an inevitable intertwining”. Artificial Intelligence and Law 1(1): 3–44.

    Google Scholar 

  63. Tillers, P. 1983. “Modern theories of relevancy”. Section 37 in Wigmore on Evidence (i.e., 'Evidence in Trials at Common Law’ by John Henry Wigmore), in Ten Volumes; Volume IA, Tillers Revision P. Tillers (revision). Boston: Little, Brown & Co., pp. 1004–1095.

    Google Scholar 

  64. Tillers, P. 1989. “Webs of things in the mind: a new science of evidence”. Review of D. Schum, Evidence and Inference for the Intelligence Analyst (2 vols). Lanham, MD: Univ. Press of America, 1987. Michigan Law Review 87(6): 1225–1258.

    Google Scholar 

  65. Tillers, P. and Green, E.D. (eds) 1988. Probability and Inference in the Law of Evidence. Dordrecht: Kluwer.

    Google Scholar 

  66. Tillers, P. and Schum, D. 1991. “A theory of preliminary fact investigation”. U.C. Davis Law Review 24(4): 931–1012.

    Google Scholar 

  67. Tomberlin, J. 1981. “Contrary-to-duty imperatives and conditional obligation”. Nous 16.

    Google Scholar 

  68. Vila, L. and Yoshino, H. 1995. “Temporal representation for legal reasoning”. Proceedings of the Third International Workshop on Legal Expert Systems for the CISG.

    Google Scholar 

  69. Williams, B. 1981. “Moral luck”. In his Moral Luck. Cambridge UP, pp. 20–39.

    Google Scholar 

  70. Wright, von, G.H. 1951. “Deontic logic”. In his Logical Studies. London: Routledge.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. CMS, Univ. of Greenwich, Wellington St., SE18 6PF, Woolwich, London, UK

    Ephraim Nissan

  2. Knowledge Systems Lab., Comp. Sci. Dept., Stanford Univ., 94305, CA, USA

    Daniel Rousseau

Authors
  1. Ephraim Nissan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Daniel Rousseau
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Zbigniew W. Raś Andrzej Skowron

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Nissan, E., Rousseau, D. (1997). Towards AI formalisms for legal evidence. In: Raś, Z.W., Skowron, A. (eds) Foundations of Intelligent Systems. ISMIS 1997. Lecture Notes in Computer Science, vol 1325. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63614-5_32

Download citation

  • DOI: https://doi.org/10.1007/3-540-63614-5_32

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63614-4

  • Online ISBN: 978-3-540-69612-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation