, Volume 34, Issue 3, pp 355–376 | Cite as

Rules for Reasoning from Knowledge and Lack of Knowledge



In this paper, the traditional view that argumentum ad ignorantiam is a logical fallacy is challenged, and lessons are drawn on how to model inferences drawn from knowledge in combination with ones drawn from lack of knowledge. Five defeasible rules for evaluating knowledge-based arguments that apply to inferences drawn under conditions of lack of knowledge are formulated. They are the veridicality rule, the consistency of knowledge rule, the closure of knowledge rule, the rule of refutation and the rule for argument from ignorance. The basic thesis of the paper is that knowledge-based arguments, including the argument from ignorance, need to be evaluated by criteria for epistemic closure and other evidential rules that are pragmatic in nature, that need to be formulated and applied differently at different stages of an investigation or discussion. The paper helps us to understand practical criteria that should be used to evaluate all arguments based on knowledge and/or ignorance.


knowledge-based reasoning argument from ignorance burden of proof fallacy consistency of knowledge epistemic closure closed world assumption 


  1. Bench-Capon, T. (1998). Specification and implementation of Toulmin dialogue game. In J. Hage et al. (Ed.), Jurix 1998: The eleventh conference (pp. 5–20). Nijmegen: Gerard Noodt Instituut.Google Scholar
  2. Branting, L. K. (2000). Reasoning with rules and precedents: A computational model of legal analysis. Dordrecht, The Netherlands: Kluwer.Google Scholar
  3. Collins, A., Warnock, E. H., Aiello N., & Miller M. L. (1975). Reasoning from incomplete knowledge. In D. G. Bobrow and A. Collins (Ed.), Representation and understanding (pp. 383–415). New York: Academic.Google Scholar
  4. Copi, I. M. (1982). Introduction to logic (6th ed.). New York: Macmillan.Google Scholar
  5. Coppin, B. (2004). Artificial intelligence illuminated. Sudbury, Massachusetts: Jones and Bartlett.Google Scholar
  6. Farley, A. M., & Freeman, K. (1995). Burden of proof in legal argumentation. In Proceedings of the 5th international conference on artificial intelligence and law (pp. 156–164). College Park: Maryland.Google Scholar
  7. Girle, R. (2003). Possible worlds. Chesham, England: Acumen.Google Scholar
  8. Hintikka, J. (1962). Knowledge and belief: An introduction to the logic of the two notions. Ithaca, New York: Cornell University Press.Google Scholar
  9. Konolige, K. (1988). On the relation between default and autoepistemic logic. Artificial Intelligence, 35, 343–382.CrossRefGoogle Scholar
  10. Leenes, R. E. (2001). Burden of proof in dialogue games and Dutch civil procedure. In Proceedings of the 8th international conference on artificial intelligence and law (pp 109–118). St. Louis, Missouri: ACM.Google Scholar
  11. Maxfield, V. A. (1981). The military decorations of the Roman army. Berkeley, California: University of California Press.Google Scholar
  12. McCarthy, J. (1980). Circumscription: A form of non-monotonic reasoning. In G. F. Luger (Ed.), Computation and intelligence: Collected readings. Cambridge, Massachusetts: MIT.Google Scholar
  13. Meyer, J.-J., & van der Hoek, W. (1995). Epistemic logic for computer science and artificial intelligence, Cambridge tracts in theoretical Computer Science 41. Cambridge, UK: Cambridge University Press.Google Scholar
  14. Reed, C., & Rowe, G. (2002). Araucaria: Software for puzzles in argument diagramming and XML. Technical report, Department of Applied Computing, University of Dundee.Google Scholar
  15. Reed, C., & Walton, D. (2004). Towards a formal and implemented model of argumentation schemes in agent communication. In I. Rahwan, P. Moraitis & C. Reed (Eds), Proceedings of ArgMAS 2004. Berlin Heidelberg New York: Springer.Google Scholar
  16. Reiter, R. (1980). A logic for default reasoning. Artificial Intelligence, 13, 81–132.CrossRefGoogle Scholar
  17. Reiter, R. (1987). Nonmonotonic reasoning. Annual Review of Computer Science, 2, 147–186.CrossRefGoogle Scholar
  18. Rowe, G., Macagno F., Reed, C., & Walton, D. (2006). Araucaria as a tool for diagramming arguments in teaching and studying philosophy. Teaching Philosophy, 29, 111–124.Google Scholar
  19. Russell, S. J., & Norvig, P. (1995). Artificial intelligence: A modern approach. Upper Saddle River, New Jersey: Prentice-Hall.Google Scholar
  20. Sterling, T. D., Rosenbaum, W. L., & Weinkam, J. J. (1995). Publication decisions revisited: The effect of the outcome of statistical tests on the decision to publish and vice versa. The American Statistician, 49, 108–112.CrossRefGoogle Scholar
  21. van Eemeren, F. H., & Grootendorst, R. (1984). Speech acts in communicative discussions. Dordrecht, The Netherlands: Foris.Google Scholar
  22. van Eemeren, F. H., & Grootendorst, R. (1987). Fallacies in pragma-dialectical perspective. Argumentation, 1, 283–301.CrossRefGoogle Scholar
  23. van Eemeren, F. H., & Grootendorst, R. (1992). Argumentation, communication and fallacies. Hillsdale, New Jersey: Erlbaum.Google Scholar
  24. van Eemeren, F. H., & Grootendorst, R. (2004). A systematic theory of argumentation. Cambridge, UK: Cambridge University Press.Google Scholar
  25. Walton, D. (1992). Nonfallacious arguments from ignorance. American Philosophical Quarterly, 29, 381–387.Google Scholar
  26. Walton, D. (1996). Arguments from ignorance. University Park, Pennsylvania: Pennsylvania State University Press.Google Scholar
  27. Walton, D. (1997). Appeal to expert opinion. University Park, Pennsylvania: Penn State University Press.Google Scholar
  28. Walton, D. (2005). Pragmatic and idealized models of knowledge and ignorance. American Philosophical Quarterly, 42, 59–69.Google Scholar
  29. Walton, D. N., & Krabbe, E. C. W. (1995). Commitment in dialogue. Albany, New York: State University of New York Press.Google Scholar
  30. Witte, C. L., Kerwin, A., & Witte, M. H. (1991). On the importance of ignorance in medical practice and education. Interdisciplinary Science Reviews, 16, 295–298.Google Scholar

Copyright information

© Springer Science + Business Media B.V. 2006

Authors and Affiliations

  1. 1.PhilosophyUniversity of WinnipegWinnipegCanada

Personalised recommendations