Advertisement

Towards a Logical Framework for Diagnostic Reasoning

  • Matteo CristaniEmail author
  • Francesco Olivieri
  • Claudio Tomazzoli
  • Margherita Zorzi
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 96)

Abstract

Diagnosis is widely used in many different disciplines to identify the nature and cause of a certain phenomenon. We present \(t\mathsf {L}\), a new logical framework able to formalise diagnostic reasoning, i.e., an hybrid learning technique based both on deduction and experiments. In this paper we introduce tL, a Labeled Modal Logic, garnishing with temporal and statistical information and a basic propositional language.

After proposing examples on how tL effectively works, we sketch the main ideas about the full deduction system à la Prawitz we are currently developing.

Keywords

Hybrid reasoning Labelled logic Temporal logic 

References

  1. 1.
    Caleiro, C., Viganò, L., Volpe, M.: A labeled deduction system for the logic UB. In: Proceedings of the 20th International Symposium on Temporal Representation and Reasoning, pp. 45–53 (2013)Google Scholar
  2. 2.
    Cristani, M., Burato, E., Gabrielli, N.: Ontology-driven compression of temporal series: a case study in SCADA technologies. In: Proceedings of DEXA Workshop, Turin, Italy (2008)Google Scholar
  3. 3.
    Cristani, M., Rotolo, A.: Meaning negotiation with defeasible logic. Smart Innov. Syst. Technol. 74, 67–76 (2017)CrossRefGoogle Scholar
  4. 4.
    Davis, R.: Diagnostic reasoning based on structure and behavior. Artif. Intell. 24(1–3), 347–410 (1984)CrossRefGoogle Scholar
  5. 5.
    Governatori, G., Olivieri, F., Rotolo, A., Scannapieco, S., Cristani, M.: Picking up the best goal an analytical study in defeasible logic. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8035, pp. 99–113 (2013)CrossRefGoogle Scholar
  6. 6.
    Governatori, G., Olivieri, F., Scannapieco, S., Cristani, M.: Superiority based revision of defeasible theories. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), LNCS, vol. 6403, pp. 104–118 (2010)CrossRefGoogle Scholar
  7. 7.
    Governatori, G., Olivieri, F., Scannapieco, S., Cristani, M.: The hardness of revising defeasible preferences. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), LNCS, vol. 8620, pp. 168–177 (2014)CrossRefGoogle Scholar
  8. 8.
    Governatori, G., Olivieri, F., Scannapieco, S., Rotolo, A., Cristani, M.: Strategic argumentation is NP-complete. Front. Artif. Intell. Appl. 263, 399–404 (2014)zbMATHGoogle Scholar
  9. 9.
    Governatori, G., Olivieri, F., Scannapieco, S., Rotolo, A., Cristani, M.: The rationale behind the concept of goal. Theory Pract. Log. Program. 16(3), 296–324 (2016)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Johnson, P.E., Durán, A.S., Hassebrock, F., Moller, J., Prietula, M., Feltovich, P.J., Swanson, D.B.: Expertise and error in diagnostic reasoning. Cogn. Sci. 5(3), 235–283 (1981)CrossRefGoogle Scholar
  11. 11.
    Lawson, A.E., Daniel, E.S.: Inferences of clinical diagnostic reasoning and diagnostic error. J. Biomed. Inform. 44(3), 402–412 (2011)CrossRefGoogle Scholar
  12. 12.
    Manning, C.D., Raghavan, P., Schütze, H.: Introduction to Information Retrieval. Cambridge University Press, New York (2008)CrossRefGoogle Scholar
  13. 13.
    Masini, A., Viganò, L., Zorzi, M.: A qualitative modal representation of quantum register transformations. In: ISMVL 2008, pp. 131–137 (2008)Google Scholar
  14. 14.
    Masini, A., Viganò, L., Zorzi, M.: Modal deduction systems for quantum state transformations. Mult. Valued Log. Soft Comput. 17(5–6), 475–519 (2011)MathSciNetzbMATHGoogle Scholar
  15. 15.
    McShane, M., Beale, S., Nirenburg, S., Jarrell, B., Fantry, G.: Inconsistency as a diagnostic tool in a society of intelligent agents. Artif. Intell. Med. 55(3), 137–148 (2012)CrossRefGoogle Scholar
  16. 16.
    McSherry, D.: Conversational case-based reasoning in medical decision making. Artif. Intell. Med. 52(2), 59–66 (2011)CrossRefGoogle Scholar
  17. 17.
    Reiter, R.: A theory of diagnosis from first principles. Artif. Intell. 32(1), 57–95 (1987)MathSciNetCrossRefGoogle Scholar
  18. 18.
    Rish, I.: An empirical study of the naive Bayes classifier. In: IJCAI Workshop on Empirical Methods in AI (2001)Google Scholar
  19. 19.
    Tomazzoli, C., Cristani, M., Karafili, E., Olivieri, F.: Non-monotonic reasoning rules for energy efficiency. J. Ambient Intell. Smart Environ. 9(3), 345–360 (2017)CrossRefGoogle Scholar
  20. 20.
    Viganò, L.: Labelled Non-Classical Logics. Kluwer Academic Publishers, Dordrecht (2000)CrossRefGoogle Scholar
  21. 21.
    Viganò, L., Volpe, M., Zorzi, M.: A branching distributed temporal logic for reasoning about entanglement-free quantum state transformations. Inf. Comput. 255, 311–333 (2017)MathSciNetCrossRefGoogle Scholar
  22. 22.
    Viganò, L., Volpe, M., Zorzi, M.: Quantum state transformations and branching distributed temporal logic. In: 21st International Workshop, WoLLIC 2014, Valparaíso, Chile, 1–4 September 2014. Lecture Notes in Computer Science, vol. 8652, pp. 1–19 (2014)zbMATHGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Matteo Cristani
    • 1
    Email author
  • Francesco Olivieri
    • 2
  • Claudio Tomazzoli
    • 1
  • Margherita Zorzi
    • 1
  1. 1.Department of Computer ScienceUniversity of VeronaVeronaItaly
  2. 2.Data61, CSIROCanberraAustralia

Personalised recommendations