Patrice C. Roy, Bruno Bouchard, Abdenour Bouzouane, Sylvain Giroux


The development towards ambient computing will stimulate research in many fields of artificial intelligence, such as activity recognition. To address this challenging issue, we present a formal activity recognition framework based on possibility theory, which is largely different from the majority of all recognition approaches proposed that are usually based on probability theory. To validate this novel alternative, we are developing an ambient agent for the cognitive assistance of an Alzheimer’s patient within a smart home, in order to identify the various ways of supporting him in carrying out his activities of daily living.


  1. Augusto, J. C. and Nugent, C. D., editors (2006). Designing Smart Homes: The Role of Artificial Intelligence, volume 4008 of LNAI. Springer.
  2. Avrahami-Zilberbrand, D. and Kaminka, G. A. (2007). Utility-based plan recognition: an extended abstract. In Proc. of AAMAS'07, pages 858-860.
  3. Baader, F., Calvanese, D., McGuinness, D. L., Nardi, D., and Patel-Schneider, P. F., editors (2007). The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press, second edition.
  4. Casas, R., Marín, R. B., Robinet, A., Delgado, A. R., Yarza, A. R., Mcginn, J., Picking, R., and Grout, V. (2008). User modelling in ambient intelligence for elderly and disabled people. In Proc. of the 11th ICCHP, number 5105 in LNCS. Springer-Verlag.
  5. Dubois, D. and Prade, H. (1988). Possibility Theory: An Approach to Computerized Processing of Uncertainty. Plenum Press.
  6. Geib, C. (2007). Plan recognition. In Kott, A. and McEneaney, W. M., editors, Adversarial Reasoning: Computational Approaches to Reading the Opponent's Mind, pages 77-100. Chapman & Hall/CRC.
  7. Kautz, H. A. (1991). A formal theory of plan recognition and its implementation. In Allen, J. F., Kautz, H. A., Pelavin, R. N., and Tenenberg, J. D., editors, Reasoning About Plans, chapter 2, pages 69-126. Morgan Kaufmann.
  8. Liao, L., Fox, D., and Kautz, H. (2004). Learning and inferring transportation routines. In Proc. of the AAAI'04, pages 348-353.
  9. Mihailidis, A., Boger, J., Canido, M., and Hoey, J. (2007). The use of an intelligent prompting system for people with dementia: A case study. ACM Interactions, 14(4):34-37.
  10. Philipose, M., Fishkin, K. P., Perkowitz, M., Patterson, D. J., Fox, D., Kautz, H., and Hähnel, D. (2004). Inferring activities from interactions with objects. IEEE Pervasive Computing: Mobile and Ubiquitous Systems, 3(4):50-57.
  11. Pollack, M. E. (2005). Intelligent technology for an aging population: The use of AI to assist elders with cognitive impairment. AI Magazine, 26(2):9-24.
  12. Roy, P., Bouchard, B., Bouzouane, A., and Giroux, S. (2009). A hybrid plan recognition model for Alzheimer's patients: Interleaved-erroneous dilemma. Web Intelligence and Agent Systems: An International Journal, 7(4):375-397.
  13. Zadeh, L. A. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1(1):3-28.

Paper Citation

in Harvard Style

C. Roy P., Bouchard B., Bouzouane A. and Giroux S. (2010). POSSIBILISTIC ACTIVITY RECOGNITION . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-674-021-4, pages 184-189. DOI: 10.5220/0002701801840189

in Bibtex Style

author={Patrice C. Roy and Bruno Bouchard and Abdenour Bouzouane and Sylvain Giroux},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},

in EndNote Style

JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
SN - 978-989-674-021-4
AU - C. Roy P.
AU - Bouchard B.
AU - Bouzouane A.
AU - Giroux S.
PY - 2010
SP - 184
EP - 189
DO - 10.5220/0002701801840189