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

Ricardo Rubiano-Cruz (), Stefan Greulich () and Christian Huchler ()
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Ricardo Rubiano-Cruz: Else Kröner Fresenius Center for Digital Health, Faculty of Medicine CGC
Stefan Greulich: Else Kröner Fresenius Center for Digital Health, Faculty of Medicine CGC
Christian Huchler: Technische Universität Dresden

A chapter in Artificial Intelligence, Data, and Decision-Making, 2026, pp 33-49 from Springer

Abstract: 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).

Keywords: Genetic algorithms; Conversational agents; Optimization; Natural language processing (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-08480-4_3

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