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A Computational Model of Habit Learning to Enable Ambient Support for Lifestyle Change

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6704))

Abstract

Agent-based applications have the potential to assist humans in their lifestyle change, for instance eliminating addictive behaviours or adopting new healthy behaviours. In order to provide adequate support, agents should take into consideration the main mechanisms underlying behaviour formation and change. Within this process habits play a crucial role: automatic behaviours that are developed unconsciously and may persist without the presence of any goals. Inspired by elements from neurological literature, a computational model of habit formation and change was developed as a basis for support agents able to assist humans in lifestyle and behaviour change. Simulations are presented showing that the model exhibits realistic human-like behaviour.

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References

  1. Ashby, F.G., Turner, B.O., Horvitz, J.C.: Cortical and basal ganglia contributions to habit learning and automaticity. Trends Cogn. Science 14, 208–215 (2010)

    Article  Google Scholar 

  2. Baldassarre, G.: A modular neural-network model of the basal ganglia’s role in learning and selecting motor behaviours. Cogn. Systems Research 3, 5–13 (2002)

    Article  Google Scholar 

  3. Bi, G., Poo, M.: Synaptic modification by correlated activity: Hebb’s postulate revisited. Annu. Rev. Neurosci. 24, 139–166 (2001)

    Article  Google Scholar 

  4. Bosse, T., Hoogendoorn, M., Klein, M.C.A., Treur, J.: An Agent-Based Generic Model for Human-Like Ambience. In: Mühlhäuser, M., Ferscha, A., Aitenbichler, E. (eds.) Constructing Ambient Intelligence: AmI 2007 Workshops Proceedings. Communications in Computer and Information Science (CCIS), vol. 11, pp. 93–103. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  5. Bosse, T., Jonker, C.M., Meij, L., van der Sharpanskykh, A., Treur, J.: Specification and Verification of Dynamics in Agent Models. International Journal of Cooperative Information Systems 18, 167–193 (2009)

    Article  Google Scholar 

  6. Bosse, T., Jonker, C.M., Meij, L., van der Treur, J.: A Language and Environment for Analysis of Dynamics by Simulation. International Journal of Artificial Intelligence Tools 16, 435–464 (2007)

    Article  Google Scholar 

  7. Cohen, M.X., Frank, M.J.: Neurocomputational models of basal ganglia function in learning, memory and choice. Behavioural Brain Research 199, 141–156 (2009)

    Article  Google Scholar 

  8. De Wit, S., et al.: Differential engagement of the ventromedial prefrontal cortex by goal-directed and habitual behaviour toward food pictures in humans. J. Neurosci. 29, 11330–11338 (2009)

    Article  Google Scholar 

  9. Duell, R., Hoogendoorn, M., Klein, M.C.A., Treur, J.: An Ambient Intelligent Agent Model using Controlled Model-Based Reasoning to Determine Causes and Remedies for Monitored Problems. In: Li, Y., Pasi, G., Zhang, C., Cercone, N., Cao, L. (eds.) Proceedings of the Second International Workshop on Human Aspects in Ambient Intelligence, HAI 2008, pp. 489–494. IEEE Computer Society Press, Los Alamitos (2008)

    Google Scholar 

  10. Everitt, B.J., Belin, D., Economidou, D., Pelloux, Y., Dalley, J.W., Robbins, T.W.: Neural mechanisms underlying the vulnerability to develop compulsive drug-seeking habits and addiction. Philos. Trans. R Soc. Lond. B Biol. Sci. 363, 3125–3135 (2008)

    Article  Google Scholar 

  11. Gerstner, W., Kistler, W.M.: Mathematical formulations of Hebbian learning. Biol. Cybern. 87, 404–415 (2002)

    Article  MATH  Google Scholar 

  12. Giles-Corti, B., Donovan, R.J.: The relative influence of individual, social and physical environment determinants of physical activity. Social Science & Medicine 54, 1793–1812 (2002)

    Article  Google Scholar 

  13. Gollwitzer, P.M., Sheeran, P.: Implementation intentions and goal achievement: A meta-analysis of effects and processes. Advances in Exp. Social Psychology 38, 69–120 (2006)

    Article  Google Scholar 

  14. Gurney, K., Prescott, T.J., Wickens, J.R., Redgrave, P.: Computational models of the basal ganglia: from robots to membranes. Trends Neurosci. 27, 453–459 (2004)

    Article  Google Scholar 

  15. Haigh, K.Z., Kiff, L.M., Myers, J., Guralnik, V., Geib, W.C., Phelps, J., Wagner, T.: The Independent LifeStyle Assistant (I.L.S.A.): AI Lessons Learned. In: Proc. of the 16th Conference on Innovative Applications of AI, San Jose, California, pp. 852–857 (2004)

    Google Scholar 

  16. Lymberis, A., De Rossi, D.E.: Wearable eHealth Systems for Personalised Health Management: State of the Art and Future Challenges. IOS Press, Amsterdam (2004)

    Google Scholar 

  17. Machado, A.: Learning the temporal Dynamics of Behaviour. Psychological Review 104, 241–265 (1997)

    Article  Google Scholar 

  18. Miller, E.K., Cohen, J.D.: An Integrative Theory of prefrontal Cortex Function. Annual Review of Neuroscience 24, 167–202 (2001)

    Article  Google Scholar 

  19. Mowrer, O.H.: Learning Theory and the Symbolic Processes. Wiley, New York (1960)

    Book  Google Scholar 

  20. Neal, D.T., Wood, W.: Automaticity in situ: Direct context cuing of habits in daily life. In: Morsella, E., Bargh, J.A., Gollwiter, P. (eds.) Oxford Handbook of Human Action, pp. 442–457. Oxford University Press, New York (2009)

    Google Scholar 

  21. Oulette, E.A., Wood, W.: Habit and Intention in everyday life: the Multiple Processes by Which Past Predicts Future Behaviour. Psychological Bulletin 124, 54–74 (1998)

    Article  Google Scholar 

  22. Pearl, J., Verma, T.S.: A theory of inferred causation. In: Principles of Knowledge Representation and Reasoning: Proc. Second Int. Conference (KR 1991), pp. 441–452 (1991)

    Google Scholar 

  23. Port, R., van Gelder, T.J.: Mind as Motion: Explorations in the Dynamics of Cognition. MIT Press, Cambridge (1995)

    Google Scholar 

  24. Quinn, J.A., Pascoe, A., Wood, W., Neal, D.T.: Can’t control yourself? Monitor those bad habits. Pers. Soc. Psychol. Bull. 36, 499–511 (2010)

    Article  Google Scholar 

  25. Skinner, B.F.: The Behaviour of Organisms: An Experimental Analysis. Appleton-Century, New York (1938)

    Google Scholar 

  26. Tang, C., Pawlak, A.P., Prokopenko, V., West, M.O.: Changes in activity of the striatum during formation of a motor habit. Eur. J. Neurosci. 25, 1212–1227 (2007)

    Article  Google Scholar 

  27. Watson, J.B.: Psychology as Behaviourist Views It. Psy. Review 20, 158–177 (1913)

    Article  Google Scholar 

  28. Webb, T.L., Sheeran, P., Luszczynska, A.: Planning to break unwanted habits: Habit strength moderates implementation intention effects on behaviour change. British Journal of Social Psychology 48, 507–523 (2009)

    Article  Google Scholar 

  29. Webb, T.L., Sheeran, P.: Mechanisms of implementation intention effects: The role of goal intentions, self-efficacy, and accessibility of plan components. British Journal of Social Psychology 47, 373–395 (2008)

    Article  Google Scholar 

  30. Wood, W., Neal, D.T.: A New Look at Habits and the Habit-Goal Interface. Psychological Review 114, 843–863 (2007)

    Article  Google Scholar 

  31. Yin, H.H., Knowlton, B.J.: The role of Basal ganglia in habit formation. Nature Reviews Neuroscience 7, 464–476 (2006)

    Article  Google Scholar 

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© 2011 Springer-Verlag Berlin Heidelberg

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Klein, M.C.A., Mogles, N., Treur, J., van Wissen, A. (2011). A Computational Model of Habit Learning to Enable Ambient Support for Lifestyle Change. In: Mehrotra, K.G., Mohan, C.K., Oh, J.C., Varshney, P.K., Ali, M. (eds) Modern Approaches in Applied Intelligence. IEA/AIE 2011. Lecture Notes in Computer Science(), vol 6704. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21827-9_14

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  • DOI: https://doi.org/10.1007/978-3-642-21827-9_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21826-2

  • Online ISBN: 978-3-642-21827-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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