Conversational Agents and Negative Lessons from Behaviourism

  • Milan GnjatovićEmail author
Part of the Intelligent Systems Reference Library book series (ISRL, volume 159)


This chapter addresses the question of whether it is enough to extract from data the knowledge needed to implement socially believable conversational agents. Contrary to the popular views, the answer is negative. In this respect, the chapter points to some shortcomings of fully data-driven approaches to dialogue management, including the lack of external criteria for the selection of dialogue corpora, and the misconception of dialogue structure and dialogue context. To point to these shortcomings is not to undervalue data-driven approaches, but to emphasize the message that big data provide only a partial account of human-machine dialogue, and thus must not remain wedded to small linguistic theory, as it is currently the case.



The presented study was sponsored by the Ministry of Education, Science and Technological Development of the Republic of Serbia (research grants III44008 and TR32035), and by the intergovernmental network EUREKA (research grant E!9944). The responsibility for the content of this article lies with the author.


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Authors and Affiliations

  1. 1.Faculty of Technical SciencesUniversity of Novi SadNovi SadSerbia

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