Abstract
In this work, it is proposed the design of a Reasoning Logical Based Intelligent Agent System Chat-bot for Dialogue Composition (DC) named E-friend, which uses Logic Programming (LP) for reasoning tasks. The main contribution is the use of Knowledge Representation Reasoning with LP theories modelling the knowledge of the user agent (beliefs, intentions, and expectations) to reason, plan and to optimally solve the DC problem. Another contribution is the design of a system component that extends the theory of mind, for the user model, with emotions to detect if the user decepts to the system or to itself. This component has the aim to alert and inform the facilitator when E-friend detects possible deceit signals from the student. E-friend was designed to help first year university students to manage stress/anxiety to optimal well-being development and attempt the prevention of depression and addictions leading. Students can interact through a chat-bot (text-based questions and answers) to help the system learns from the user, at the same time the user learns from itself improving mental health well-being.
L. A. M. Moreno and D. Rojas-Velázquez—Independent Researcher.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
We do not consider this issue in this paper.
- 2.
A functionality learned from Woebot chat-bot presented in the work of Fitzpatrick Kathleen et al. referred in [16].
- 3.
We thank the support of Psychologist Andres Munguia Barcenas.
- 4.
TheE-friendapplicationisavailableinhttps://github.com/luis-angel-montiel-moreno/efriend.
References
Baskar, J., Janols, R., Guerrero, E., Nieves, J.C., Lindgren, H.: A multipurpose goal model for personalised digital coaching. In: Montagna, S., Abreu, P.H., Giroux, S., Schumacher, M.I. (eds.) A2HC/AHEALTH -2017. LNCS (LNAI), vol. 10685, pp. 94–116. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-70887-4_6
Baskar, J., Lindgren, H., et al.: Cognitive architecture of an agent for human-agent dialogues. In: Corchado, J.M. (ed.) PAAMS 2014. CCIS, vol. 430, pp. 89–100. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07767-3_9
Bell, S., Wood, C., Sarkar, A.: Perceptions of chatbots in therapy. In: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems, p. LBW1712 (2019)
Bendig, E., Erb, B., Schulze-Thuesing, L., Baumeister, H.: The next generation: chatbots in clinical psychology and psychotherapy to foster mental health-a scoping review. Verhaltenstherapie 1–13 (2019)
Diano, F., Ferrata, F., Calabretta, R.: The development of a mindfulness-based mobile application to learn emotional self-regulation. In: PSYCHOBIT (2019)
Dyoub, A., Costantini, S., Lisi, F.A.: Towards ethical machines via logic programming 306, 333–339 (2019)
Fuentes, M.: The broken trap: the problematic of Sexual Addiction. Ediciones del Verbo Encarnado (2015). https://books.google.com.mx/books?id=Su2zCgAAQBAJ
Galindo, J.A., Dupuy-Chessa, S., Céret, É.: Toward a UI adaptation approach driven by user emotions (2017)
Greenberg, A.E., Smeets, P., Zhurakhovska, L.: Lying, guilt, and shame. Technical report, Mimeo (2014)
Inkster, B., Sarda, S., Subramanian, V.: An empathy-driven, conversational artificial intelligence agent (Wysa) for digital mental well-being: real-world data evaluation mixed-methods study. JMIR mHealth uHealth 6(11), e12106 (2018)
Jacobs, T.L., et al.: Intensive meditation training, immune cell telomerase activity, and psychological mediators. Psychoneuroendocrinology 36(5), 664–681 (2011)
Jingar, M., Lindgren, H.: Tangible communication of emotions with a digital companion for managing stress: an exploratory co-design study. In: Proceedings of the 7th International Conference on Human-Agent Interaction, pp. 28–36 (2019)
Luksha, P., Cubista, J., Laszlo, A., Popovich, M., Ninenko, I.: Educational ecosystems for societal transformation (2017)
Mostafa, M., Crick, T., Calderon, A.C., Oatley, G.: Incorporating emotion and personality-based analysis in user-centered modelling. In: Bramer, M., Petridis, M. (eds.) Research and Development in Intelligent Systems XXXIII, pp. 383–389. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-47175-4_29
Ortony, A., Clore, G.L., Collins, A.: The Cognitive Structure of Emotions. Cambridge University Press, Cambridge (1990)
Osorio, M., Zepeda, C., Carballido, J.L.: MyUBot: towards an artificial intelligence agent system chat-bot for well-being and mental health. In: Accepted in Artificial Intelligence for HEaLth, PersonaLized MedIcine aNd WEllbeing Workshop at ECAI 2020 (2020)
Osorio, M., Zepeda, C., Carballido, J.L.: Towards a virtual companion system to give support during confinement. In: CONTIE (2020)
Osorio, M., Zepeda, C., Castillo, H., Cervantes, P., Carballido, J.L.: My university e-partner. In: CONTIE, pp. 150–1503 (2019)
Osorio, M., Cuevas, V.: Updates in answer set programming: an approach based on basic structural properties. Theory Pract. Log. Program. 7(4), 451–479 (2007)
Poirson, E., Cunha, C.D.: A recommender approach based on customer emotions. Expert Syst. Appl. 122, 281–288 (2019)
Rachman, S.: Betrayal: a psychological analysis. Behav. Res. Ther. 48(4), 304–311 (2010)
Ribeiro, I.J., Pereira, R., et al.: Stress and quality of life among university students: a systematic literature review. Health Prof. Educ. 4(2), 70–77 (2018)
Sarkadi, S., Panisson, A.R., Bordini, R.H., McBurney, P., Parsons, S., Chapman, M.: Modelling deception using theory of mind in multi-agent systems. AI Commun. 32(4), 287–302 (2019)
Sarlej, M.: A lesson learned: using emotions to generate stories with morals. Ph.D. thesis, Computer Science & Engineering, University of New South Wales (2014)
Schaub, T., Woltran, S.: Answer set programming unleashed! KI 32(2–3), 105–108 (2018). https://doi.org/10.1007/s13218-018-0550-z
Vrij, A.: Why professionals fail to catch liars and how they can improve. Legal Criminol. Psychol. 9(2), 159–181 (2004)
Walton, D.: The place of dialogue theory in logic, computer science and communication studies. Synthese 123(3), 327–346 (2000)
World Health Organization: World health organization. WHO (2020). https://www.who.int/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Galindo, M.J.O., Moreno, L.A.M., Rojas-Velázquez, D., Nieves, J.C. (2021). E-Friend: A Logical-Based AI Agent System Chat-Bot for Emotional Well-Being and Mental Health. In: Sarkadi, S., Wright, B., Masters, P., McBurney, P. (eds) Deceptive AI. DeceptECAI DeceptAI 2020 2021. Communications in Computer and Information Science, vol 1296. Springer, Cham. https://doi.org/10.1007/978-3-030-91779-1_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-91779-1_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-91778-4
Online ISBN: 978-3-030-91779-1
eBook Packages: Computer ScienceComputer Science (R0)