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Analyzing Speech Acts Based on Dynamic Normative Logic

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New Frontiers in Artificial Intelligence (JSAI-isAI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8417))

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Abstract

In a conversation, different kinds of speech acts are performed. Logic for communication has to deal with these various kinds of speech acts ([5]: 52). Additionally, for interpretation of conversations, it will be appropriate to take shared beliefs among communication partners into consideration. In this paper, we show that this problem can be dealt with in a framework that is a dynamic extension of the logic for normative systems.

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Notes

  1. 1.

    A characteristic of LNS is its dynamic behaviors. LNS is quite flexible, so that LNS can be applied to describe complex normative problems including ethical problems. See [12, 13].

  2. 2.

    The main difference between two versions of LNS consists in the use of some notions in (1a). We use now the notion belief base instead of propositional system. Some effects of this change will become visible, when we start to analyze interactions among normative systems of different agents.

  3. 3.

    The many-sorted logic is reducible to FOL. Thus, this difference is not essential.

  4. 4.

    In this paper, we require the consistency of T\(\cup \)OB from two reasons, namely to justify the claim that obligation implies permission and to smoothly describe rule-following behaviors.

  5. 5.

    For the development of the dynamic epistemic logic, you nay consult [2]. There, van Benthem characterizes the epistemic logic as logic of semantic information ([2]: 21). Compared to DEL, our approach in this paper is more syntactically orientated.

  6. 6.

    As we see in the next section, a normative state of a person can be influenced by that of other persons.

  7. 7.

    Note that all of theorems in Theorem 2 are applicable to \(ns(X>Y, t)\) and \(ns(X>Y>Z, t)\) as well, because they are all normative systems that satisfy all conditions in Definition 1.

  8. 8.

    Note that \(\mathbf B q \leftrightarrow \mathbf BB q\) is a theorem of the doxastic logic D45.

  9. 9.

    In fact the notion of collective agent should be more carefully defined. See discussions about extended agents in [17, 18]. For mereology, you may consult [25]. For four-dimensionalism, see [24]. For four-dimensional mereology, see [8, 11].

  10. 10.

    GEM is the strongest mereological system. For GEM, you may consult [3] and [27].

  11. 11.

    I did this kind of proposal in [9].

  12. 12.

    The classical work for semantics of demonstratives is formalized by D. Kaplan [7]. I proposed some improvements of Kaplan’s framework [13, 15, 16].

  13. 13.

    This replacement of *-terms by singular terms creates interpretations of demonstratives and indexicals.

  14. 14.

    From (4b) follows: \(\mathbf O _{ns(A+B,t(n))} \exists t (\textit{go-to-school} (B, t) \wedge t(n) \le t)\) \(\Rightarrow \) \(\mathbf O _{ns(A,t(n))} \exists t (\textit{go-to-school} (B, t) \wedge t_f(n) \le t)\) & \(\mathbf O _{ns(B,t(n))} \exists t (\textit{go-to-school} (B, t) \wedge t_f(n) \le t)\).

  15. 15.

    This claim implies a rejection of social constructivism of physical facts. For discussions about this topic, see [10, 22].

  16. 16.

    The AGM theory is an established formal framework for belief revision [4]. However, the revision of normative systems is quite complex and difficult to deal with the AGM theory.

  17. 17.

    Discussions in [2] are restricted on various kinds of extension of proposi-tional modal logics, while DNL is a framework based on FOL.

  18. 18.

    This research was supported by Global COE Program Center of Human-Friendly Robotics Based on Cognitive Neuroscience of the Ministry of Education, Culture, Sports, Science and Technology, Japan, and by Grant-in-for Scientific Research, Scientific Research C (24520014): The Construction of Philosophy of Science based on the Theory of Multiple Languages. Finally, I would like to thank two reviewers for useful comments.

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Authors and Affiliations

  1. Graduate School of Human Sciences, Osaka University, Suita, Japan

    Yasuo Nakayama

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  1. Yasuo Nakayama
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Correspondence to Yasuo Nakayama .

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Editors and Affiliations

  1. Seikei University, Musashino-shi, Tokyo, Japan

    Yukiko Nakano

  2. National Institute of Informatics Research Division, Tokyo, Japan

    Ken Satoh

  3. Ochanomizu University, Tokyo, Japan

    Daisuke Bekki

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Nakayama, Y. (2014). Analyzing Speech Acts Based on Dynamic Normative Logic. In: Nakano, Y., Satoh, K., Bekki, D. (eds) New Frontiers in Artificial Intelligence. JSAI-isAI 2013. Lecture Notes in Computer Science(), vol 8417. Springer, Cham. https://doi.org/10.1007/978-3-319-10061-6_7

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  • DOI: https://doi.org/10.1007/978-3-319-10061-6_7

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