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A Multi-Agent Depth Bounded Boolean Logic

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Abstract

Recent developments in the formalization of reasoning, especially in computational settings, have aimed at defining cognitive and resource bounds to express limited inferential abilities. This feature is emphasized by Depth Bounded Boolean Logics, an informational logic that models epistemic agents with inferential abilities bounded by the amount of information they can use. However, such logics do not model the ability of agents to make use of information shared by other sources. The present paper provides a first account of a Multi-Agent Depth Bounded Boolean Logic, defining agents whose limited inferential abilities can be increased through a dynamic operation of becoming informed by other data sources.

This research was funded by the Department of Philosophy “Piero Martinetti” of the University of Milan under the project “Departments of Excellence 2018–2022” awarded by the Ministry of Education, University and Research (MIUR); and supported by the Austrian Science Fund (FWF) project ByzDEL (P33600). The authors wish to thank Marcello D’Agostino and Pere Pardo for comments on previous versions of this work.

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Notes

  1. 1.

    We use here a two-value valuation function v on formulas as a mapping to truth and falsity. Its formal definition, extended to a three-valued function, is postponed to Sect. 3.

  2. 2.

    This example is based on an unpublished one formulated by Marcello D’Agostino.

  3. 3.

    The two operators reflect the distinction between an alethically neutral and a veridical conception of information, see [17] and [11] respectively. Technically, it is possible to reformulate the present monotonic version of MA-DBBL without the I operator without loss of expressiveness. We keep it both in the language to preserve the mentioned conceptual distinction, and because it offers the basis for a planned extension of the present system with contradictory information updates.

  4. 4.

    We stress here that while in single agent DBBL the depth of the reasoning process is given by nested applications of RB by the agent, in MA-DBBL are the instances of RB indexed by distinct agents that determine such depth.

References

  1. Allo, P.: The logic of ‘being informed’ revisited and revised. Philos. Stud. 153(3), 417–434 (2011). https://doi.org/10.1007/s11098-010-9516-1

    Article  MathSciNet  Google Scholar 

  2. van Benthem, J.: Dynamic logic for belief revision. J. Appl. Non-Classical Logics 17(2), 129–155 (2007). https://doi.org/10.3166/jancl.17.129-155

    Article  MathSciNet  MATH  Google Scholar 

  3. Ceolin, D., Primiero, G.: A granular approach to source trustworthiness for negative trust assessment. In: Meng, W., Cofta, P., Jensen, C.D., Grandison, T. (eds.) IFIPTM 2019. IAICT, vol. 563, pp. 108–121. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-33716-2_9

    Chapter  Google Scholar 

  4. D’Agostino, M.: Depth-bounded logic for realistic agents. Logic Philos. Sci. 11, 3–57 (2013)

    Google Scholar 

  5. D’Agostino, M.: Informational semantics, non-deterministic matrices and feasible deduction. In: Fernández, M., Finger, M. (eds.) Proceedings of the 8th Workshop on Logical and Semantic Frameworks, LSFA 2013, São Paulo, Brazil, 2–3 September 2013, Electronic Notes in Theoretical Computer Science, vol. 305, pp. 35–52. Elsevier (2013). URL https://doi.org/10.1016/j.entcs.2014.06.004

  6. D’Agostino, M.: Semantic information and the trivialization of logic: Floridi on the scandal of deduction. Information 4(1), 33–59 (2013). https://doi.org/10.3390/info4010033

    Article  Google Scholar 

  7. D’Agostino, M.: Analytic inference and the informational meaning of the logical operators. Logique Anal. 227, 407–437 (2014)

    MathSciNet  MATH  Google Scholar 

  8. D’Agostino, M.: An informational view of classical logic. Theor. Comput. Sci. 606, 79–97 (2015). https://doi.org/10.1016/j.tcs.2015.06.057

    Article  MathSciNet  MATH  Google Scholar 

  9. van Ditmarsch, H., Halpern, J., van der Hoek, W., Kooi, B.: Handbook of Epistemic Logic. College Publications, London (2015)

    MATH  Google Scholar 

  10. Ditmarsch, H., van der Hoek, W., Kooi, B.: Dynamic Epistemic Logic and Philosophy Of Science. Springer, Berlin (2007)

    MATH  Google Scholar 

  11. Floridi, L.: The logic of being informed. Logique et Analyse 49(196), 433–460 (2006). http://www.jstor.org/stable/44085232

  12. Floridi, L.: Semantic information and the correctness theory of truth. Erkenntnis 74(2), 147–175 (2011). https://doi.org/10.1007/s10670-010-9249-8

    Article  MATH  Google Scholar 

  13. Stegenga, J.: Information quality in clinical research. In: Floridi, L., Illari, P. (eds.) The Philosophy of Information Quality. SL, vol. 358, pp. 163–182. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07121-3_9

    Chapter  Google Scholar 

  14. Larese, C.: The principle of analyticity of logic, a philosophical and formal perspective. Ph.D. thesis, Scuola Normale Superiore, Classe di Scienze Umane (2019)

    Google Scholar 

  15. Meyer, J.J.C., Hoek, W.v.d.: Epistemic Logic for AI and Computer Science. Cambridge Tracts in Theoretical Computer Science. Cambridge University Press (1995). https://doi.org/10.1017/CBO9780511569852

  16. Primiero, G.: An epistemic constructive definition of information. Logique et Analyse 50(200), 391–416 (2007)

    MathSciNet  MATH  Google Scholar 

  17. Primiero, G.: An epistemic logic for becoming informed. Synthese 167(2), 363–389 (2009). https://doi.org/10.1007/s11229-008-9413-8

  18. Primiero, G.: A logic of negative trust. J. Appl. Non Class. Logics 30(3), 193–222 (2020). https://doi.org/10.1080/11663081.2020.1789404

    Article  MathSciNet  Google Scholar 

  19. Primiero, G., Raimondi, F., Bottone, M., Tagliabue, J.: Trust and distrust in contradictory information transmission. Appl. Netw. Sci. 2(1), 1–30 (2017). https://doi.org/10.1007/s41109-017-0029-0

    Article  Google Scholar 

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Correspondence to Giorgio Cignarale .

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Cignarale, G., Primiero, G. (2021). A Multi-Agent Depth Bounded Boolean Logic. In: Cleophas, L., Massink, M. (eds) Software Engineering and Formal Methods. SEFM 2020 Collocated Workshops. SEFM 2020. Lecture Notes in Computer Science(), vol 12524. Springer, Cham. https://doi.org/10.1007/978-3-030-67220-1_14

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  • DOI: https://doi.org/10.1007/978-3-030-67220-1_14

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