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Formalizing Explanatory Dialogues

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Book cover Scalable Uncertainty Management (SUM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9310))

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Abstract

Many works have proposed architectures and models to incorporate explanation within agent’s design for various reasons (i.e. human-agent teamwork improvement, training in virtual environment [10], belief revision [8], etc.), with this novel architectures a problematic is emerged: how to communicate these explanations in a goal-directed and rule-governed dialogue system? In this paper we formalize Walton’s \(\mathtt CE\) dialectical system of explanatory dialogues in the framework of Prakken. We extend this formalization within the Extended \(\mathtt CE\) system by generalizing the protocol and incorporating a general account of dialectical shifts. More precisely, we show how a shift to any dialogue type can take place, as an example we describe a shift to argumentative dialogue with the goal of giving the explainee the possibility to challenge explainer’s explanations. In addition, we propose the use of commitment and understanding stores to avoid circular and inconsistent explanations and to judge the success of explanation. We show that the dialogue terminates, under specific conditions, in finite steps and the space complexity of the stores evolves polynomially in the size of the explanatory model.

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Notes

  1. 1.

    Throughout the paper we always use Greek letters \(\psi , \varphi , \phi \), etc. as metavariables for syntactically different well-formed formula (wff), and \(\varGamma \), \(\varGamma _0\),\(\ldots \) for sets of wffs.

  2. 2.

    See [16] for a full description of the protocol.

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Acknowledgment

Financial support from the French National Research Agency (ANR) for the project DUR-DUR (ANR-13-ALID-0002) is gratefully acknowledged. We are also grateful to Nouredine Tamani for his valuable comments on the paper.

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Correspondence to Abdallah Arioua .

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Arioua, A., Croitoru, M. (2015). Formalizing Explanatory Dialogues. In: Beierle, C., Dekhtyar, A. (eds) Scalable Uncertainty Management. SUM 2015. Lecture Notes in Computer Science(), vol 9310. Springer, Cham. https://doi.org/10.1007/978-3-319-23540-0_19

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  • DOI: https://doi.org/10.1007/978-3-319-23540-0_19

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