- Alan Dix ORCID:orcid.org/0000-0002-5242-769315 &
- Genovefa Kefalidou ORCID:orcid.org/0000-0002-2889-756416
Part of the book series:Lecture Notes in Computer Science ((LNCS,volume 13230))
Included in the following conference series:
634Accesses
Abstract
Regret seems like a very negative emotion, sometimes even debilitating. However, emotions usually have a purpose – in the case of regret to help us learn from past mistakes. In this paper we first present an informal cognitive account of the way regret is built from a wide range of both primitive and more sophisticated mental abilities. The story includes Skinner-level learning, imagination, emotion, and counter-factual reasoning. When it works well this system focuses attention on aspects of past events where a small difference in behaviour would have made a big difference in outcome – precisely the most important lessons to learn. The paper then takes elements of this cognitive account and creates a computational model, which can be applied in simple learning situations. We find that even this simplified model boosts machine learning reducing the number of required training samples by a factor of 3–10. This has theoretical implications in terms of understanding emotion and mechanisms that may cast light on related phenomena such as creativity and serendipity. It also has potential practical applications in improving machine leaning and maybe even alleviating dysfunctional regret.
This is a preview of subscription content,log in via an institution to check access.
Access this chapter
Subscribe and save
- Get 10 units per month
- Download Article/Chapter or eBook
- 1 Unit = 1 Article or 1 Chapter
- Cancel anytime
Buy Now
- Chapter
- JPY 3498
- Price includes VAT (Japan)
- eBook
- JPY 5719
- Price includes VAT (Japan)
- Softcover Book
- JPY 7149
- Price includes VAT (Japan)
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Agrawal, M., Peterson, J.C., Griffiths, T.L.: Scaling up psychology via scientific regret minimization. Proc. Natl. Acad. Sci.117(16), 8825–8835 (2020).https://doi.org/10.1073/pnas.1915841117
Azevedo, R., Hadwin, A.F.: Scaffolding self-regulated learning and metacognition-implications for the design of computer-based scaffolds. Instr. Sci.33(5/6), 367–379 (2005)
Baker-Sennett, J., Matusov, E., Rogoff, B.: Planning as developmental process. Adv. Child Dev. Behav.24, 253–281 (1993)
Baldi, P., Atiya, A.F.: How delays affect neural dynamics and learning. IEEE Trans. Neural Netw.5(4), 612–621 (1994)
Bandura, A., Walters, R.H.: Social Learning Theory, vol. 1. Prentice Hall, Englewood Cliffs (1977)
Bitterman, M.: Classical conditioning since Pavlov. Rev. Gen. Psychol.10(4), 365–376 (2006)
Blum, A., Mansour, Y.: Learning, regret minimization, and equilibria. In: Nisan, N., Roughgarden, T., Tardos, E., Vazirani, V.V. (eds.) Algorithmic Game Theory, pp. 79–102. Cambridge University Press, Cambridge (2007).https://doi.org/10.1017/CBO9780511800481.006
Brown, N., Lerer, A., Gross, S., Sandholm, T.: Deep counterfactual regret minimization. In: International Conference on Machine Learning, pp. 793–802. PMLR (2019).https://proceedings.mlr.press/v97/brown19b.html
Butz, M.V., Achimova, A., Bilkey, D., Knott, A.: Event-predictive cognition: a root for conceptual human thought (2021).https://doi.org/10.1111/tops.12522
Byrne, R.M.: Cognitive processes in counterfactual thinking about what might have been. In: Medin, D. (ed.) The Psychology of Learning and Motivation: Advances in Research and Theory, pp. 105–154. Academic Press, San Diego (1997)
Byrne, R.M.: Mental models and counterfactual thoughts about what might have been. Trends Cogn. Sci.6(10), 426–431 (2002)
Byrne, R.M.: The Rational Imagination: How People Create Alternatives to Reality. MIT Press, Cambridge (2007)
Clark, R.E.: The classical origins of Pavlov’s conditioning. Integr. Physiol. Behav. Sci.39(4), 279–294 (2004)
Connolly, T., Zeelenberg, M.: Regret in decision making. Curr. Dir. Psychol. Sci.11(6), 212–216 (2002)
Dix, A.: The adaptive significance of regret (2005).https://alandix.com/academic/essays/regret.pdf, unpublished essay
Dykes, J.: The carbon footprint of AI and cloud computing. Geographical (2020).https://geographical.co.uk/nature/energy/item/3876-the-carbon-footprint-of-ai-and-cloud-computing
Egan, K.: Memory, imagination, and learning: connected by the story. Phi Delta Kappan70(6), 455–459 (1989)
EPSRC: Human-like computing: Report of a workshop held on 17 & 18 February 2016, Bristol, UK (2016)
Epstude, K., Roese, N.J.: The functional theory of counterfactual thinking. Pers. Soc. Psychol. Rev.12(2), 168–192 (2008)
Fehrer, E.: Effects of amount of reinforcement and of pre-and postreinforcement delays on learning and extinction. J. Exp. Psychol.52(3), 167 (1956)
Freitag, C., Berners-Lee, M., Widdicks, K., Knowles, B., Blair, G.S., Friday, A.: The real climate and transformative impact of ICT: a critique of estimates, trends, and regulations. Patterns2(9), 1–18 (2021).https://doi.org/10.1016/j.patter.2021.100340
Friedman, S.L., Scholnick, E.K.: The Developmental Psychology of Planning: Why, How, and When Do We Plan? Psychology Press, London (2014)
Kahneman, D., Miller, D.T.: Norm theory: comparing reality to its alternatives. Psychol. Rev.93(2), 136–153 (1986).https://doi.org/10.1037/0033-295X.93.2.136
Kahneman, D., Tversky, A.: Prospect theory: an analysis of decision under risk. Econometrica47(2), 263–291 (1979).https://doi.org/10.2307/1914185.http://www.jstor.org/stable/1914185
Lattal, K.A.: Delayed reinforcement of operant behavior. J. Exp. Anal. Behav.93(1), 129–139 (2010).https://doi.org/10.1901/jeab.2010.93-129
Loomes, G., Sugden, R.: Regret theory: an alternative theory of rational choice under uncertainty. Econ. J.92(368), 805–824 (1982).https://doi.org/10.2307/2232669
MacIntyre, P., Gregersen, T.: Emotions that facilitate language learning: the positive-broadening power of the imagination. Stud. Second Lang. Learn. Teach.2(2), 193–213 (2012).https://pressto.amu.edu.pl/index.php/ssllt/article/view/5009/5229
Markman, K.D., McMullen, M.N.: A reflection and evaluation model of comparative thinking. Pers. Soc. Psychol. Rev.7(3), 244–267 (2003)
Markman, K.D., McMullen, M.N., Elizaga, R.A.: Counterfactual thinking, persistence, and performance: a test of the reflection and evaluation model. J. Exp. Soc. Psychol.44(2), 421–428 (2008)
McCormack, T., Feeney, A., Beck, S.R.: Regret and decision-making: a developmental perspective. Curr. Dir. Psychol. Sci.29(4), 346–350 (2020).https://doi.org/10.1177/0963721420917688
McSweeney, F.K., Bierley, C.: Recent developments in classical conditioning. J. Consum. Res.11(2), 619–631 (1984)
Muggleton, S., Chater, N.: Human-Like Machine Intelligence. University Press, Oxford (2021)
O’Connor, E., McCormack, T., Feeney, A.: Do children who experience regret make better decisions? A developmental study of the behavioral consequences of regret. Child Dev.85(5), 1995–2010 (2014).https://doi.org/10.1111/cdev.12253
Pearce, J.M., Bouton, M.E.: Theories of associative learning in animals. Annu. Rev. Psychol.52(1), 111–139 (2001).https://doi.org/10.1146/annurev.psych.52.1.111
Sanna, L.J., Stocker, S.L., Clarke, J.A.: Rumination, imagination, and personality: specters of the past and future in the present. In: Chang, E.C., Sanna, L.J. (eds.) Virtue, Vice, and Personality: The Complexity of Behavior, pp. 105–124. American Psychological Association (2003).https://doi.org/10.1037/10614-007
Shalev-Shwartz, S., et al.: Online learning and online convex optimization. Found. Trends Mach. Learn.4(2), 107–194 (2011).https://doi.org/10.1561/2200000018
Skinner, B.: Operant conditioning. In: The Encyclopedia of Education, vol. 7, pp. 29–33
Smith, T.A., Kimball, D.R.: Learning from feedback: spacing and the delay-retention effect. J. Exp. Psychol. Learn. Mem. Cogn.36(1), 80 (2010)
Staddon, J.E., Cerutti, D.T.: Operant conditioning. Annu. Rev. Psychol.54(1), 115–144 (2003)
Touretzky, D.S., Saksida, L.M.: Operant conditioning in Skinnerbots. Adapt. Behav.5(3–4), 219–247 (1997)
Touretzky, D., Saksida, L.: Skinnerbots. In: Maes, P., Mataric, M., Meyer, J.A., Pollack, J., Wilson, S.W. (eds.) From Animals to Animats 4: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior, pp. 285–294. MIT Press, Cambridge (1996)
Van de Ven, N., Zeelenberg, M.: Regret aversion and the reluctance to exchange lottery tickets. J. Econ. Psychol.32(1), 194–200 (2011)
Weick, K.E.: The role of imagination in the organizing of knowledge. Eur. J. Inf. Syst.15(5), 446–452 (2006).https://doi.org/10.1057/palgrave.ejis.3000634
Zeelenberg, M., Pieters, R.: Consequences of regret aversion in real life: the case of the Dutch postcode lottery. Organ. Behav. Hum. Decis. Process.93(2), 155–168 (2004)
Zeelenberg, M., Van Dijk, W.W., Manstead, A.S.R., der Pligt, J.: The experience of regret and disappointment. Cogn. Emot.12(2), 221–230 (1998)
Zhang, Z., Ji, X.: Regret minimization for reinforcement learning by evaluating the optimal bias function. In: Advances in Neural Information Processing Systems, vol. 32 (2019).https://proceedings.neurips.cc/paper/2019/file/9e984c108157cea74c894b5cf34efc44-Paper.pdf
Zinkevich, M., Johanson, M., Bowling, M., Piccione, C.: Regret minimization in games with incomplete information. In: Proceedings of the 20th International Conference on Neural Information Processing Systems (NIPS 2007), pp. 1729–1736. Curran Associates Inc., Red Hook (2007)
Author information
Authors and Affiliations
Computational Foundry, Swansea University, Swansea, Wales, UK
Alan Dix
School of Computing and Mathematical Sciences, University of Leicester, Leicester, UK
Genovefa Kefalidou
- Alan Dix
You can also search for this author inPubMed Google Scholar
- Genovefa Kefalidou
You can also search for this author inPubMed Google Scholar
Corresponding author
Correspondence toGenovefa Kefalidou.
Editor information
Editors and Affiliations
Nazarbayev University, Nur-Sultan, Kazakhstan
Antonio Cerone
University of L'Aquila, L'Aquila, Italy
Marco Autili
Mälardalen University, Västerås, Sweden
Alessio Bucaioni
Aarhus University, Aarhus, Denmark
Cláudio Gomes
University of Urbino, Urbino, Italy
Pierluigi Graziani
University of Pisa, Pisa, Italy
Maurizio Palmieri
Sapienza University of Rome, Rome, Italy
Marco Temperini
Tokyo University of Agriculture and Technology, Tokyo, Japan
Gentiane Venture
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Dix, A., Kefalidou, G. (2022). Regret from Cognition to Code. In: Cerone, A.,et al. Software Engineering and Formal Methods. SEFM 2021 Collocated Workshops. SEFM 2021. Lecture Notes in Computer Science, vol 13230. Springer, Cham. https://doi.org/10.1007/978-3-031-12429-7_2
Download citation
Published:
Publisher Name:Springer, Cham
Print ISBN:978-3-031-12428-0
Online ISBN:978-3-031-12429-7
eBook Packages:Computer ScienceComputer Science (R0)
Share this paper
Anyone you share the following link with will be able to read this content:
Sorry, a shareable link is not currently available for this article.
Provided by the Springer Nature SharedIt content-sharing initiative