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Toward Conscious-Like Conversational Agents

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Toward Robotic Socially Believable Behaving Systems - Volume II

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 106))

Abstract

Although considerable effort has been already devoted to studying various aspects of human-machine interaction, we are still a long way from developing socially believable conversational agents. This paper identifies some of the main causes of the current state in the field: (i) socially believable behaviour of a technical system is misinterpreted as a functional requirement, rather than a qualitative, (ii) the currently prevalent statistical approaches cannot address research problems of managing human-machine interaction that require some sort of contextual analysis, and (iii) the structure of human-machine interaction is unjustifiably reduced to a task structure. In addition, we propose a way to address these pitfalls. We consider the capability of a technical system to simulate fundamental features of human consciousness as one of the key desiderata to perform socially believable behaviour. In line with this, the paper discusses the possibilities for the computational realization of (iv) unified interpretation, (v) learning through interaction, and (vi) context-dependent perception in the context of human-machine interaction.

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Notes

  1. 1.

    And possibly other contexts (e.g., the user’s electroencelographic activity, etc.).

  2. 2.

    Apart from the fact that the study of architecture to support intelligent behaviour may be one of the most ill-defined enterprises in the field of artificial intelligence [26].

  3. 3.

    In our previous work, we refer to these two groups as to focus stimuli and negative reinforcement stimuli. However, the terms stimuli and inhibitors reflect more appropriately the dichotomy between these groups.

  4. 4.

    The research question of short-term adaptation of the system’s dialogue strategy is addressed in [23, 24].

  5. 5.

    The practice of long-term collection of the user’s data opens many important ethical questions that are out of the scope of this paper. However, these questions still remain to be properly addressed.

  6. 6.

    Only for the purpose of illustration, the lower end of the range of significant retrieval costs for a given balanced focus tree can be estimated as the ratio of the height of the focus tree to the number of all nodes in the focus tree.

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Acknowledgments

The presented study was sponsored by the Ministry of Education, Science and Technological Development of the Republic of Serbia under the Research grants III44008 and TR32035. The responsibility for the content of this paper lies with the authors.

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Authors and Affiliations

  1. Graduate School of Computer Sciences, John Naisbitt Univeristy, Bulevar Umetnosti 29, 11070, Belgrade, Serbia

    Milan Gnjatović

  2. Faculty of Technical Sciences, University of Novi Sad, Dositeja Obradovića 6, 21000, Novi Sad, Serbia

    Milan Gnjatović

  3. Faculty of Technical Sciences, University of Novi Sad, Trg Dositeja Obradovića 6, 21000, Novi Sad, Serbia

    Branislav Borovac

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  1. Milan Gnjatović
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  2. Branislav Borovac
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Correspondence to Milan Gnjatović .

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Editors and Affiliations

  1. Department of Psychology, Seconda Università di Napoli and IIASS, Caserta, Italy

    Anna Esposito

  2. Data Sci. Inst., Faculty of Sci. & Tech., Bournemouth University, Poole, United Kingdom

    Lakhmi C. Jain

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Gnjatović, M., Borovac, B. (2016). Toward Conscious-Like Conversational Agents. In: Esposito, A., Jain, L. (eds) Toward Robotic Socially Believable Behaving Systems - Volume II . Intelligent Systems Reference Library, vol 106. Springer, Cham. https://doi.org/10.1007/978-3-319-31053-4_4

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  • DOI: https://doi.org/10.1007/978-3-319-31053-4_4

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