User-Like Bots for Cognitive Automation: A Survey

Habtom Kahsay Gidey, Peter Hillmann, Andreas Karcher, Alois Knoll

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Software bots have attracted increasing interest and popularity in both research and society. Their contributions span automation, digital twins, game characters with conscious-like behavior, and social media. However, there is still a lack of intelligent bots that can adapt to the variability and dynamic nature of digital web environments. Unlike human users, they have difficulty understanding and exploiting the affordances across multiple virtual environments. Despite the hype, bots with human user-like cognition do not currently exist. Chatbots, for instance, lack situational awareness on the digital platforms where they operate, preventing them from enacting meaningful and autonomous intelligent behavior similar to human users. In this survey, we aim to explore the role of cognitive architectures in supporting efforts towards engineering software bots with advanced general intelligence. We discuss how cognitive architectures can contribute to creating intelligent software bots. Furthermore, we highlight key architectural recommendations for the future development of autonomous, user-like cognitive bots.

Original languageEnglish
Title of host publicationMachine Learning, Optimization, and Data Science - 9th International Conference, LOD 2023, Revised Selected Papers
EditorsGiuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Panos M. Pardalos, Renato Umeton
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages15
ISBN (Print)9783031539657
StatePublished - 2024
Event9th International Conference on Machine Learning, Optimization, and Data Science, LOD 2023 - Grasmere, United Kingdom
Duration: 22 Sep 202326 Sep 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14506 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference9th International Conference on Machine Learning, Optimization, and Data Science, LOD 2023
Country/TerritoryUnited Kingdom


  • cognitive architecture
  • cognitive automation
  • software bot


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