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GA4CA: Genetic Algorithms for the Creation and Design of Conversational Agents

In: Artificial Intelligence, Data, and Decision-Making

Author

Listed:
  • Ricardo Rubiano-Cruz

    (Else Kröner Fresenius Center for Digital Health, Faculty of Medicine CGC
    Technische Universität Dresden)

  • Stefan Greulich

    (Else Kröner Fresenius Center for Digital Health, Faculty of Medicine CGC
    Technische Universität Dresden)

  • Christian Huchler

    (Technische Universität Dresden)

Abstract

User frustration is one negative consequence of human–computer interaction caused by bad interpretations and insufficient adaptation to user preferences. In this scope, genetic algorithms (GAs) might offer some insights to mitigate this problem. Hence, we conducted a systematic review to identify the implementation of GAs in the field of the design of conversational agents (CAs). Our results displayed that the literature focuses on three clusters mainly using evolutionary algorithms, and binary-coded GAs for natural language processing (NLP).

Suggested Citation

  • Ricardo Rubiano-Cruz & Stefan Greulich & Christian Huchler, 2026. "GA4CA: Genetic Algorithms for the Creation and Design of Conversational Agents," Lecture Notes in Information Systems and Organization, in: Christoph M. Flath & Gunther Gust & Frédéric Thiesse & Axel Winkelmann (ed.), Artificial Intelligence, Data, and Decision-Making, pages 33-49, Springer.
    • Handle: RePEc:spr:lnichp:978-3-032-08480-4_3
    DOI: 10.1007/978-3-032-08480-4_3
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