Evidential Reasoning



When a suspect appears in front of a criminal court, there is a high probability that he will be found guilty. In the USA, statistics for recent years show that the conviction rate in federal courts is roughly 90%, and in Japan reaches as high a rate as 99%.



This chapter has been developed in the context of the project “Designing and Understanding Forensic Bayesian Networks with Arguments and Scenarios,” funded in the NWO Forensic Science program ( The first author would like to thank Infosys Limited which made possible his stay at the Institute for Advanced Study in Princeton for the academic year 2016–17 during which parts of this chapter were written. The second author would like to thank the Isaac Newton Institute for Mathematical Sciences at the University of Cambridge for its hospitality during the program “Probability and Statistics in Forensic Science” which was supported by EPSRC Grant Number EP/K032208/1. The authors would like to thank Ronald Allen, Alex Biedermann, Christian Dahlman, and Norman Fenton for helpful comments and suggestions on an earlier draft.


  1. Allen, R.J. 2010. No plausible alternative to a plausible story of guilt as the rule of decision in criminal cases. In Prueba y Esandares de Prueba en el Derecho, ed. J. Cruz, and L. Laudan. Mexico: Instituto de Investigaciones Filosoficas-UNAM.Google Scholar
  2. Allen, R.J., and M.S. Pardo. 2007. The problematic value of mathematical models of evidence. Journal of Legal Studies 36 (1): 107–140.CrossRefGoogle Scholar
  3. Allen, R.J., and A. Stein. 2013. Evidence, probability and the burden of proof. Arizona Law Journal 55: 557–602.Google Scholar
  4. Allen, R.J., W.J. Stuntz, J.L. Hoffmann, D.A. Livingston, A.D. Leipold, and T.L. Meares. 2016. Comprehensive criminal procedure, 3rd ed. New York, N.Y.: Wolters Kluwer.Google Scholar
  5. Anderson, T., D. Schum, and W. Twining. 2005. Analysis of Evidence, 2nd ed. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  6. Balding, D.J. 1999. When can a DNA profile be regarded as unique? Science & Justice 39.CrossRefGoogle Scholar
  7. Balding, D.J. 2005. Weight-of-evidence for forensic DNA profiles. West Sussex: Wiley.CrossRefGoogle Scholar
  8. Balding, D.J., and P. Donnely. 1996. Evaluating DNA profile evidence when the suspect is identified through a database search. Journal of Forensic Science 41: 603–607.CrossRefGoogle Scholar
  9. Bennett, W.L., and M.S. Feldman. 1981. Reconstructing reality in the courtroom. London: Tavistock Feldman.Google Scholar
  10. Bernoulli, J. 1713. Ars Conjectandi.Google Scholar
  11. Bex, F.J. 2011. Arguments, stories and criminal evidence: A formal hybrid theory. Berlin: Springer.CrossRefGoogle Scholar
  12. Bex, F.J., P.J. van Koppen, H. Prakken, and B. Verheij. 2010. A hybrid formal theory of arguments, stories and criminal evidence. Artificial Intelligence and Law 18: 1–30.CrossRefGoogle Scholar
  13. Bex, F.J., and B. Verheij. 2013. Legal stories and the process of proof. Artificial Intelligence and Law 21 (3): 253–278.CrossRefGoogle Scholar
  14. Biedermann, A., T. Hicks, F. Taroni, C. Champod, C. Aitken. On the use of the likelihood ratio for forensic evaluation: Response to Fenton, et al. 2014. Science and Justice 54 (4): 316–318.Google Scholar
  15. Bondarenko, A., P.M. Dung, R.A. Kowalski, and F. Toni. 1997. An abstract, argumentation-theoretic approach to default reasoning. Artificial Intelligence 93: 63–101.CrossRefGoogle Scholar
  16. BonJour, L. 1985. The structure of empirical knowledge. Cambridge, MA: Harvard University Press.Google Scholar
  17. Bovens, L., and S. Hartmann. 2003a. Bayesian Epistemology. Oxford: Oxford University Press.Google Scholar
  18. Bovens, L., and S. Hartmann. 2003b. Solving the riddle of coherence. Mind 112: 601–633.CrossRefGoogle Scholar
  19. Carnap, R. 1950. Logical foundations of probability. Chicago, IL: University of Chicago Press.Google Scholar
  20. Cheng, E. 2013. Reconceptualizing the burden of proof. Yale Law Journal 122 (5): 1104–1371.Google Scholar
  21. Cohen, L.J. 1977. The probable and the provable. Oxford: Clarendon Press.CrossRefGoogle Scholar
  22. Cook, R., I.W. Evett, G. Jackson, P.J. Jones, and J.A. Lambert. 1998. A hierarchy of propositions: Deciding which level to address in casework. Science and Justice 38 (4): 231–239.CrossRefGoogle Scholar
  23. Crump, D. 2009. Eyewitness corroboration requirements as protections against wrongful conviction: The hidden questions. Ohio State Journal of Criminal Law 7 (1): 361–376.Google Scholar
  24. Crupi, V. 2015. Confirmation. In Stanford encyclopedia of philosophy, ed. E.N. Zalta. Stanford University.Google Scholar
  25. Darwiche, A. 2009. Modeling and reasoning with bayesian networks. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  26. Dawid, A.P. 1987. The difficulty about conjunction. Journal of the Royal Statistical Society. Series D (The Statistician) 36(2/3):91–92.CrossRefGoogle Scholar
  27. Dawid, A.P. 2002. Bayes’s theorem and weighing evidence by juries. In Bayes’s Theorem, vol. 113, 71–90, Oxford: Oxford University Press.Google Scholar
  28. Dawid, A.P. 2010. Beware of the DAG! In JMLR workshop and conference proceedings: Volume 6. Causality: Objectives and assessment (NIPS 2008 workshop), eds. I. Guyon, D. Janzing, and B. Schölkopf, 59–86.
  29. Dawid, A.P., W. Twining, and M. Vasiliki (eds.). 2011. Evidence, inference and enquiry. Oxford: Oxford University Press.Google Scholar
  30. Dung, P.M. 1995. On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence 77: 321–357.CrossRefGoogle Scholar
  31. Evett, I., G. Jackson, J.A. Lambert, and S. McCrossan. 2000. The impact of the principles of evidence interpretation on the structure and content of statements. Science and Justice 40 (4): 233–239.CrossRefGoogle Scholar
  32. Fenton, N., D. Berger, D. Lagnado, M. Neil, and A. Hsu. 2014. When “neutral” evidence still has probative value (with implications from the barry george case). Science and Justice 54 (4): 274–287.CrossRefGoogle Scholar
  33. Fenton, N., M. Neil, and D. Berger. 2016. Bayes and the law. Annual Review of Statistics and Its Application 3.CrossRefGoogle Scholar
  34. Fenton, N.E. 2011. Science and law: Improve statistics in court. Nature 479: 36–37.CrossRefGoogle Scholar
  35. Fenton, N.E., and M.D. Neil. 2013. Risk assessment and decision analysis with Bayesian networks. Boca Raton, FL: CRC Press.Google Scholar
  36. Fenton, N.E., M.D. Neil, and D.A. Lagnado. 2013. A general structure for legal arguments about evidence using Bayesian Networks. Cognitive Science 37: 61–102.CrossRefGoogle Scholar
  37. Finkelstein, M.O., and W.B. Fairley. 1970. A Bayesian approach to identification evidence. Harvard Law Review 83: 489–517.CrossRefGoogle Scholar
  38. Finkelstein, M.O., and B. Levin. 2001. Statistics for lawyers. Berlin: Springer.Google Scholar
  39. Fisher, G. 2008. Evidence, 2nd ed. New York, N.Y.: Foundation Press.Google Scholar
  40. Fitelson, B. 1999. The plurality of Bayesian measures of confirmation and the problem of measure sensitivity. Philosophy of Science 66: 362–378.CrossRefGoogle Scholar
  41. Freeman, J.B. 1991. Dialectics and the macrostructure of arguments. A theory of argument structure. Berlin: Foris.CrossRefGoogle Scholar
  42. Friedman, M. 1974. Explanation and scientific understanding. Journal of Philosophy 71: 5–19.CrossRefGoogle Scholar
  43. Friedman, R.D. 1987. Route analysis of credibility and hearsay. The Yale Law Journal 97 (4): 667–742.CrossRefGoogle Scholar
  44. Friedman, R.D. 2000. A presumption of innocence, not of even odds. Stanford Law Review 52: 873–887.CrossRefGoogle Scholar
  45. Frumkin, D., A. Wasserstrom, A. Davidson, and A. Grafit. 2009. Authentication of forensic DNA samples. Forensic Science International: Genetics 4 (2): 95–103.CrossRefGoogle Scholar
  46. Gabbay, D.M., C.J. Hogger, and J.A. Robinson (eds.). 1994. Handbook of logic in artificial intelligence and logic programming. Volume 3. Nonmonotonic reasoning and uncertain reasoning. Oxford: Clarendon Press.Google Scholar
  47. Gastwirth, J.L. (ed.). 2012. Statistical Science in the Courtroom. Berlin: Springer.Google Scholar
  48. Gordon, T.F., H. Prakken, and D.N. Walton. 2007. The Carneades model of argument and burden of proof. Artificial Intelligence 171 (10–15): 875–896.CrossRefGoogle Scholar
  49. Gordon, T.F., and D.N. Walton. 2009. Proof burdens and standards. In Argumentation in artificial intelligence, ed. I. Rahwan, and G.R. Simari, 239–258. Berlin: Springer.CrossRefGoogle Scholar
  50. Griffin, L.K. 2013. Narrative, truth, trial. Georgetown Law Journal 101: 281–335.Google Scholar
  51. Haack, S. 2008. Warrant, causation, and the atomist of evidence law. Journal of Social Epistemology 5: 253–265.CrossRefGoogle Scholar
  52. Haack, S. 2014. Legal probabilism: An epistemological dissent. In Science, proof, and truth in the law, ed. Evidence Matters, 47–77. Cambridge: Cambridge University Press.Google Scholar
  53. Hacking, I. 2001. An introduction to probability and inductive logic. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  54. Hage, J.C. 1997. Reasoning with rules. An essay on legal reasoning and its underlying logic. Dordrecht: Kluwer.Google Scholar
  55. Hage, J.C. 2000. Dialectical models in artificial intelligence and law. Artificial Intelligence and Law 8: 137–172.CrossRefGoogle Scholar
  56. Hamer, D. 2004. Probabilistic standards of proof, their complements and the errors that are expected to flow from them. University of New England Law Journal 1 (1): 71–107.Google Scholar
  57. Hempel, C., and P. Oppenheim. 1948. Studies in the logic of explanation. Philosophy of Science 15: 135–175.CrossRefGoogle Scholar
  58. Hepler, A.B., A.P. Dawid, and V. Leucari. 2007. Object-oriented graphical representations of complex patterns of evidence. Law, Probability and Risk 6 (1–4): 275–293.CrossRefGoogle Scholar
  59. Hicks, T., J. Buckleton, J.-A. Bright, and D. Taylor. 2016. A framework for interpreting evidence. In Forensic DNA Evidence Interpretation (second edition), ed. J. Buckleton, J.-A. Bright, and D. Taylor. Boca Raton, FL: CRC Press.Google Scholar
  60. Ho, H.L. 2008. Philosophy of evidence law. Oxford: Oxford University Press.CrossRefGoogle Scholar
  61. Jensen, F.V., and T.D. Nielsen. 2007. Bayesian networks and decision graphs. Berlin: Springer.CrossRefGoogle Scholar
  62. Kadane, J.B., and D.A. Schum. 1996. A probabilistic analysis of the Sacco and Vanzetti evidence. Chichester: Wiley.Google Scholar
  63. Kaplan, J. 1968. Decision theory and the fact-finding process. Stanford Law Review 20: 1065–1092.CrossRefGoogle Scholar
  64. Kaplow, L. 2012. Burden of proof. Yale Law Journal 121 (4): 738–1013.Google Scholar
  65. Kaptein, H., H. Prakken, and B. Verheij (eds.). 2009. Legal evidence and proof: statistics, stories, logic (Applied legal philosophy series). Farnham: Ashgate.Google Scholar
  66. Kaye, D.H. 1986. Do we need a calculus of weight to understand proof beyond a reasonable doubt? Boston University Law Review 66: 657–672.Google Scholar
  67. Kaye, D.H. 1993. DNA evidence: Probability, population genetics and the courts. Harvard Journal of Law and Technology 7: 101–172.Google Scholar
  68. Kaye, D.H. 1999. Clarifying the burden of persuasion: What Bayesian rules do and not do. International Commentary on Evidence 3: 1–28.Google Scholar
  69. Kaye, D.H. 2010. The double helix and the law of evidence. Cambridge, Mass.: Harvard University Press.Google Scholar
  70. Kaye, D.H. 2013. Beyond uniqueness: the birthday paradox, source attribution and individualization in forensic science. Law, Probability and Risk 12 (1): 3–11.CrossRefGoogle Scholar
  71. Kaye, D.H., and G.F. Sensabaugh. 2000. Reference guide on DNA evidence. In Reference manual on scientific evidence, 2nd ed., 576–585. Washington, D.C.: Federal Judicial Center.Google Scholar
  72. Keppens, J. 2012. Argument diagram extraction from evidential Bayesian networks. Artificial Intelligence and Law 20: 109–143.CrossRefGoogle Scholar
  73. Keppens, J., and B. Schafer. 2006. Knowledge based crime scenario modelling. Expert Systems with Applications 30 (2): 203–222.CrossRefGoogle Scholar
  74. Kirschner, P.A., S.J.B. Shum, and C.S. Carr. 2003. Visualizing argumentation: Software tools for collaborative and educational sense-making. Berlin: Springer.CrossRefGoogle Scholar
  75. Koehler, J.J. 1993. Error and exaggeration in the presentation of DNA evidence in trial. Jurimetrics Journal 34: 21–39.Google Scholar
  76. Koehler, J.J., and M.J. Saks. 2010. Individualization claims in forensic science: Still unwarranted. Brooklyn Law Review 75 (4): 1187–1208.Google Scholar
  77. Laplace, P.-S. 1814. Essai Philosophique sur les Probabilités.Google Scholar
  78. Laudan, L. 2006. Truth, error, and criminal law: An essay in legal epistemology. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  79. Lempert, R.O. 1977. Modeling relevance. Michigan Law Review 75 (5/6): 1021–1057.CrossRefGoogle Scholar
  80. Lipton, P. 1991. Inference to the best explanation. New York, N.Y.: Routledge.CrossRefGoogle Scholar
  81. Loftus, E.F. 1996. Eyewitness testimony (revised edition). Cambridge, MA: Harvard University Press.Google Scholar
  82. Méndez, M.A. 2008. Evidence: The California code and the Federal rules, 4th ed. Eagan, MN: Thomson West.Google Scholar
  83. Mortera, J., and P. Dawid. 2007. Probability and evidence. In Handbook of probability theory, ed. T. Rudas. Los Angeles, CA: Sage.Google Scholar
  84. Nance, D.A. 2016. The burdens of proof: Discriminatory power, weight of evidence, and tenacity of belief. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  85. Nesson, C.R. 1979. Reasonable doubt and permissive inferences: The value of complexity. Harvard Law Review 92 (6): 1187–1225.CrossRefGoogle Scholar
  86. NRC. 1996. The evaluation of forensic DNA evidence. Washington, D.C.: National Academy Press.Google Scholar
  87. Pardo, M.S., and R.J. Allen. 2008. Juridical proof and the best explanation. Law and Philosophy 27: 223–268.CrossRefGoogle Scholar
  88. Pearl, J. 1988. Probabilistic reasoning in intelligent systems: Networks of plausible inference. San Mateo, CA: Morgan Kaufmann.Google Scholar
  89. Pearl, J. 2000/2009. Causality: Models, reasoning and inference, 2nd ed. Cambridge: Cambridge University Press.Google Scholar
  90. Pennington, N., and R. Hastie. 1993a. Inside the juror, chap. The story model for juror decision making, 192–221. Cambridge: Cambridge University Press.Google Scholar
  91. Pennington, N., and R. Hastie. 1993b. Reasoning in explanation-based decision making. Cognition 49 (1–2): 123–163.CrossRefGoogle Scholar
  92. Picinali, F. 2013. Two meanings of “reasonableness”: Dispelling the “floating” reasonable doubt. Modern Law Review 76 (5): 845–875.CrossRefGoogle Scholar
  93. Pollock, J.L. 1987. Defeasible reasoning. Cognitive Science 11 (4): 481–518.CrossRefGoogle Scholar
  94. Pollock, J.L. 1995. Cognitive Carpentry: A blueprint for how to build a person. Cambridge, MA: The MIT Press.Google Scholar
  95. Prakken, H. 1997. Logical tools for modelling legal argument. A study of defeasible reasoning in law. Dordrecht: Kluwer.CrossRefGoogle Scholar
  96. Prakken, H. 2005. A study of accrual of arguments, with applications to evidential reasoning. In Proceedings of the tenth international conference on artificial intelligence and law, 85–94, New York (New York): ACM Press.Google Scholar
  97. Prakken, H. 2010. An abstract framework for argumentation with structured arguments. Argument and Computation 1 (2): 93–124.CrossRefGoogle Scholar
  98. Prakken, H., and G. Sartor. 2007. Formalising arguments about the burden of persuasion. In Proceedings of the 11th international conference on artificial intelligence and law, 97–106, New York, N.Y.: ACM Press.Google Scholar
  99. Prakken, H., and G. Sartor. 2009. A logical analysis of burdens of proof. In Legal evidence and proof: Statistics, stories, logic, chap. 9, ed. H. Kaptein, H. Prakken, and B. Verheij, 223–253, Farnham: Ashgate.Google Scholar
  100. Prakken, H., and G.A.W. Vreeswijk. 2002. Logics for defeasible argumentation. In Handbook of philosophical logic, vol. 4, 2nd ed. D.M. Gabbay, and F. Guenthner, 218–319. Dordrecht: Kluwer Academic Publishers.Google Scholar
  101. Redmayne, M. 2015. Character evidence in the criminal trial. Oxford: Oxford University Press.CrossRefGoogle Scholar
  102. Reed, C., and G. Rowe. 2004. Araucaria: Software for argument analysis, diagramming and representation. International Journal of AI Tools 14 (3–4): 961–980.CrossRefGoogle Scholar
  103. Robertson, B., and G.A. Vignaux. 1995. DNA evidence: Wrong answers or wrong questions? Genetica 96: 145–152.CrossRefGoogle Scholar
  104. Roberts, P., and A. Zuckerman. 2010. Criminal evidence, 2nd ed. Oxford: Oxford University Press.Google Scholar
  105. Salmon, W. 1984. Scientific explanation and the causal structure of the world. Princeton, N.J.: Princeton University Press.Google Scholar
  106. Schank, R., and R. Abelson. 1977. Scripts, plans, goals and understanding, an inquiry into human knowledge structures. Hillsdale: Lawrence Erlbaum.Google Scholar
  107. Schneps, L., and C. Colmez. 2013. Math on trial: How numbers get used and abused in the courtroom. New York, N.Y.: Basic Books.Google Scholar
  108. Schum, D.A. 1994. The evidential foundations of probabilistic reasoning. New York, N.Y.: Wiley.Google Scholar
  109. Schum, D.A., and S. Starace. 2001. The evidential foundations of probabilistic reasoning. Evanston, Il.: Northwestern University Press.Google Scholar
  110. Shapiro, B. 1991. Beyond reasonable doubt and probable cause: Historical perspectives on the Anglo-American law of evidence. Oakland, Calif.: University of California Press.Google Scholar
  111. Simari, G.R., and R.P. Loui. 1992. A mathematical treatment of defeasible reasoning and its applications. Artificial Intelligence 53: 125–157.CrossRefGoogle Scholar
  112. Simons, D.J., and C.F. Chabris. 1999. Gorillas in our minds: Sustained inattention blindness for dynamic events. Perception 28: 1059–1074.CrossRefGoogle Scholar
  113. Skyrms, B. 2000. Choice and chance: An introduction to inductive logic, 4th ed. Belmont, CA: Wadsworth.Google Scholar
  114. Stein, A. 2005. Foundations of evidence law. Oxford: Oxford University Press.CrossRefGoogle Scholar
  115. Swinburne, R. (ed.). 2002. Bayes’s theorem. Oxford: Oxford University Press.Google Scholar
  116. Tanaka, J.W., and M.J. Farah. 1993. Parts and whole in face recognition. The Quarterly Journal of Experimental Psychology 46A (3): 225–245.CrossRefGoogle Scholar
  117. Taroni, F., A. Biedermann, S. Bozza, P. Garbolino, and C. Aitken. 2014. Statistics in practice. In Bayesian networks for probabilistic inference and decision analysis in forensic science, 2nd ed. Chichester: Wiley.Google Scholar
  118. Taroni, F., C. Champod, and P. Margot. 1998. Forerunners of Bayesianism in early forensic science. Jurimetrics 38: 183–200.Google Scholar
  119. Thagard, P. 1989. Explanatory coherence. Behavioral and Brain Sciences 12: 435–502.CrossRefGoogle Scholar
  120. Thagard, P. 2001. Coherence in thought and action. Cambridge, MA: The MIT Press.Google Scholar
  121. Thompson, S.G. 2008. Beyond a reasonable doubt? reconsidering uncorroborated eyewitness identification testimony. UC Davis Law Review 41: 1487–1545.Google Scholar
  122. Thompson, W.C., and E.L. Schumann. 1987. Interpretation of statistical evidence in criminal trials: The prosecutor’s fallacy and the defense attorney’s fallacy. Law and Human Behavior 11: 167–187.CrossRefGoogle Scholar
  123. Thompson, W.C., F. Taroni, and C.G.G. Aitken. 2003. How the probability of a false positive affects the value of DNA evidence. Journal of Forensic Science 48: 47–54.Google Scholar
  124. Thomson, J.J. 1986. Liability and individualized evidence. Law and Contemporary Problems 49 (3): 199–219.CrossRefGoogle Scholar
  125. Thomson, P. 1980. Margaret Thatcher: A new illusion. Perception 9 (4): 483–484.CrossRefGoogle Scholar
  126. Tillers, P. 2011. Trial by mathematics-reconsidered. Law, Probability and Risk 10: 167–173.CrossRefGoogle Scholar
  127. Timmer, S.T., J.J. Meyer, H. Prakken, S. Renooij, and B. Verheij. 2017. A two-phase method for extracting explanatory arguments from Bayesian networks. International Journal of Approximate Reasoning 80: 475–494.CrossRefGoogle Scholar
  128. Toulmin, S.E. 1958. The uses of argument. Cambridge: Cambridge University Press.Google Scholar
  129. Tribe, L. 1971. Trial by mathematics: Precision and ritual in the legal process. Harvard Law Review 84: 1329–1393.CrossRefGoogle Scholar
  130. van Eemeren, F.H., B. Garssen, E.C.W. Krabbe, A.F. Snoeck Henkemans, B. Verheij, and J.H.M. Wagemans. 2014a. Chapter 11: Argumentation in artificial intelligence. In Handbook of argumentation theory. Berlin: Springer.Google Scholar
  131. van Eemeren, F.H., B. Garssen, E.C.W. Krabbe, A.F. Snoeck Henkemans, B. Verheij, and J.H.M. Wagemans. 2014b. Handbook of argumentation theory. Berlin: Springer.CrossRefGoogle Scholar
  132. van Gelder, T. 2003. Enhancing deliberation through computer supported argument visualization. In Visualizing argumentation: Software tools for collaborative and educational sense-making, ed. P.A. Kirschner, S.J.B. Shum, and C.S. Carr, 97–115. New York, N.Y.: Springer.CrossRefGoogle Scholar
  133. Velleman, D. 2003. Narrative explanation. The Philosophical Review 112 (1): 1–25.CrossRefGoogle Scholar
  134. Verheij, B. 1996. Rules, reasons, arguments. Formal studies of argumentation and defeat.. Maastricht: Dissertation Universiteit Maastricht.Google Scholar
  135. Verheij, B. 2003. DefLog: on the logical interpretation of prima facie justified assumptions. Journal of Logic and Computation 13 (3): 319–346.CrossRefGoogle Scholar
  136. Verheij, B. 2005. Virtual arguments. On the design of argument assistants for lawyers and other arguers. The Hague: T.M.C. Asser Press.Google Scholar
  137. Verheij, B. 2014. To catch a thief with and without numbers: Arguments, scenarios and probabilities in evidential reasoning. Law, Probability and Risk 13: 307–325.CrossRefGoogle Scholar
  138. Verheij, B. 2017. Proof with and without probabilities. correct evidential reasoning with presumptive arguments, coherent hypotheses and degrees of uncertainty. Artifical Intelligence and Law 25(1):127–154.CrossRefGoogle Scholar
  139. Verheij, B., F.J. Bex, S.T. Timmer, C.S. Vlek, J.J. Meyer, S. Renooij, and H. Prakken. 2016. Arguments, scenarios and probabilities: Connections between three normative frameworks for evidential reasoning. Law, Probability and Risk 15 (1): 35–70.CrossRefGoogle Scholar
  140. Vlek, C.S., H. Prakken, S. Renooij, and B. Verheij. 2014. Building Bayesian Networks for legal evidence with narratives: a case study evaluation. Artifical Intelligence and Law 22 (4): 375–421.CrossRefGoogle Scholar
  141. Vlek, C.S., H. Prakken, S. Renooij, and B. Verheij. 2016. A method for explaining Bayesian Networks for legal evidence with scenarios. Artifical Intelligence and Law 24 (3): 285–324.CrossRefGoogle Scholar
  142. Vreeswijk, G.A.W. 1997. Abstract argumentation systems. Artificial Intelligence 90: 225–279.CrossRefGoogle Scholar
  143. Vrij, A. 2008. Detecting lies and deceit: The psychology of lying and the implications for professional practice. Chichester: Wiley.Google Scholar
  144. Wagenaar, W.A., P.J. van Koppen, and H.F.M. Crombag. 1993. Anchored narratives: The psychology of criminal evidence. London: Harvester Wheatsheaf.Google Scholar
  145. Walton, D.N., and E. Krabbe. 1995. Commitment in dialogue. Basic concepts of interpersonal reasoning. Albany (New York): State University of New York Press.Google Scholar
  146. Walton, D.N., C. Reed, and F. Macagno. 2008. Argumentation schemes. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  147. Wasserman, D. 2008. Forensic DNA typing. In A companion to genethics, ed. J. Burley, and J. Harris. Malden, MA: Blackwell.Google Scholar
  148. Weir, B.S. 2007. The rarity of DNA profiles. The Annals of Applied Statistics 1: 358–370.CrossRefGoogle Scholar
  149. Wells, G.L. 1992. Naked statistical evidence of liability: Is subjective probability enough? Journal of Personality and Social Psychology 62: 793–752.CrossRefGoogle Scholar
  150. Wells, G.L., A. Memon, and S.D. Penrod. 2006. Eyewitness evidence: Improving its probative value. Psychological Science in the Public Interest 7 (2): 45–75.CrossRefGoogle Scholar
  151. Whitman, J.Q. 2008. The origins of reasonable doubt: Theological roots of the criminal trial. New Haven, CT: Yale University Press.Google Scholar
  152. Wigmore, J.H. 1913. The principles of judicial proof as given by logic, psychology, and general experience, and illustrated in judicial trials. Second edition 1931, third edition “The science of judicial proof” 1937. Boston, MA: Little, Brown and Company.Google Scholar
  153. Woodward, J. 2014. Scientific explanation. In The Stanford encyclopedia of philosophy, ed. E.N. Zalta. Stanford University.Google Scholar
  154. Zabell, S.L. 2005. Fingerprint evidence. Journal of Law and Policy 13: 143–179.Google Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Lehman College - City University of New YorkBronxUSA
  2. 2.Faculty of Science and EngineeringUniversity of GroningenGroningenThe Netherlands

Personalised recommendations