Abstract
Intelligent rooms comprise hardware devices that support human activities in a room and software that has some level of control over the devices. “Intelligent” implies that the room is considered to behave in an intelligent manner or includes some aspect of artificial intelligence in its implementation. The focus of this paper is intelligent sensed environments, including rooms or interactive spaces that display adaptive behaviour through learning and motivation. We present motivated agent models that incorporate machine learning in which the motivation component eliminates the need for a benevolent teacher to prepare problem specific reward functions or training examples. Our model of motivation is based on concepts of “curiosity”, “novelty” and “interest”. We explore the potential for this model through the implementation of a curious place.
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References
Aylett, R.A., et al.: Agent-based continuous planning. In: Proceedings of the 19th Workshop of the UK Planning and Scheduling Special Interest Group (PLANSIG 2000) (2000)
Berlyne, D.E.: Aesthetics and psychobiology. Prentice-Hall, Englewood Cliffs (1971)
Brdiczka, O., Reignier, P., Crowley, J.: Supervised learning of an abstract context model for an intelligent environment. In: Proceedings of the Joint sOc-EUSAI Conference, Grenoble (2005)
Brooks, R.A., Coen, M., Dang, D., DeBonet, J., Kramer, J., Lozano-Perez, T., Mellor, J., Pook, P., Stauffer, C., Stein, L., Torrance, M., Wessler, M.: The Intelligent Room Project. In: Proceedings of the Second International Cognitive Technology Conference (CT 1997), Aizu, Japan, pp. 271–279 (1997)
Canamero, L.: Modeling motivations and emotions as a basis for intelligent behaviour. In: Proceedings of the First International Symposium on Autonomous Agents. ACM Press, New York (1997)
Coen, M.H.: Design Principles for Intelligent Environments. In: Proceedings of the Fifteenth National / Tenth Conference on Artificial Intelligence / Innovative Applications of Artificial Intelligence, Madison, Wisconsin, United States, pp. 547–554 (1998)
Deci, E., Ryan, R.: Intrinsic motivation and self-determination in human behaviour. Plenum Press, New York (1985)
Gemeinboeck, P.: Negotiating the In-Between: Space, Body and the Condition of the Virtual. Crossings - Electronic Journal of Art and Technology 4(1) (2004)
Dieterich, H., Malinowski, U., Khme, T., Schneider-Hufschmidt, M.: State of the art in adaptive user interfaces. In: Schneider-Hufschmidt, M., Khme, T., Malinowski, U. (eds.) Adaptive User Interfaces: Principle and Practice. North-Holland, Amsterdam (1993)
Dzeroski, S., De Raedt, L., Blockeel, H.: Relational reinforcement learning. In: International Conference on Inductive Logic Programming (1998)
Gershenson, C.: Artificial Societies of Intelligent Agents, Bachelor of Engineering Thesis, Fundacion Arturo Rosenblueth (2001)
Graesser, A., Van Lehn, K., Rose, C., Jordan, P., Harter, D.: Intelligent tutoring systems with conversational dialogue. AI Magazine 22(4), 39–52 (2001)
Green, R.G., Beatty, W.W., Arkin, R.M.: Human motivation: physiological, behavioural and social approaches. Allyn and Bacon, Inc., Massachussets (1984)
Hammond, T., Gajos, K., Davis, R., Shrobe, H.: An Agent-Based System for Capturing and Indexing Software Design Meetings. In: Gero, J.S., Brazier, F.M.T. (eds.) Agents in Design 2002, Key Centre of Design Computing and Cognition, University of Sydney, pp. 203–218 (2002)
Horvitz, E., Breese, J., Heckerman, D., Hovel, D., Rommelse, K.: The Lumiere project: Bayesian user modelling for inferring the goals and needs of software users. In: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, pp. 256–265 (1998)
Kandel, E.R., Schwarz, J.H., Jessell, T.M.: Essentials of neural science and behaviour. Appleton and Lang, Norwalk (1995)
Kaplan, F., Oudeyer, P.-Y.: Motivational principles for visual know-how development. In: Proceedings of the 3rd international workshop on Epigenetic Robotics: Modeling cognitive development in robotic systems, Lund University Cognitive Studies (2003)
Kohonen, T.: Self-organisation and associative memory. Springer, Berlin (1993)
Krueger, M., Gionfriddo, T., et al.: Videoplace: an artificial reality. In: Human Factors in Computing Systems, CHI 1985. ACM Press, New York (1985)
Luck, M., d’Inverno, M.: Motivated behaviour for goal adoption. In: Zhang, C., Lukose, D. (eds.) DAI 1998. LNCS (LNAI), vol. 1544, pp. 58–73. Springer, Heidelberg (1998)
Maher, M.L., Merrick, K., Macindoe, O.: Can designs themselves be creative? In: Computational and Cognitive Models of Creative Design, Heron Island, pp. 111–135 (2005)
Marsland, S., Nehmzow, U., Shapiro, J.: A real-time novelty detector for a mobile robot. In: EUREL European Advanced Robotics Systems Masterclass and Conference (2000)
Merceron, A.: Languages and Logic. Pearson Education, Australia (2001)
Norman, T.J., Long, D.: Goal creation in motivated agents. In: Intelligent agents: theories, architectures and languages. Springer, Heidelberg (1995)
Russel, J., Norvig, P.: Artificial intelligence: a modern approach. Prentice Hall Inc., Englewood Cliffs (1995)
Saunders, R., Gero, J.S.: Designing for Interest and Novelty: Motivating Design Agents. In: de Vries, B., van Leeuwen, J., Achten, H. (eds.) CAADFutures 2001, pp. 725–738. Kluwer, Dordrecht (2001)
Saunders, R., Gero, J.S.: Curious agents and situated design evaluations. In: Gero, J.S., Brazier, F.M.T. (eds.) Agents In Design: Key Centre of Design Computing and Cognition, pp. 133–149. University of Sydney, Sydney (2002)
Schmidhuber, J.: A possibility for implementing curiosity and boredom in model-building neural controllers. In: The International Conference on Simulation of Adaptive behaviour: From Animals to Animats (1991)
Schmill, M., Cohen, P.: A motivational system that drives the development of activity. In: AAAMAS. ACM, Bologna (2002)
Singh, S., Barto, A.G., Chentanez, N.: Intrinsically Motivated Reinforcement Learning (2004) (accessed, April 7, 2004), http://www.eecs.umich.edu/~baveja/Papers/FinalNIPSIMRL.pdf
Sloman, A., Croucher, M.: Why robots will have emotions. In: Proceedings of the 7th International Joint Conference on Artificial Intelligence, Vancouver (1981)
Stanley, J.C.: Computer simulation of a model of habituation. Nature 261, 146–148 (1976)
Sutton, R.S., Barto, A.G.: Reinforcement learning: an introduction. MIT Press, Cambridge (2000)
Wang, Y., Huber, M., et al.: User-guided reinforcement learning of robot assistive tasks for an intelligent environment. In: Proceedings of the IEEE/RJS International Conference on Intelligent Robots and Systems. IEEE, Las Vegas (2003)
Watkins, C.: Learning from delayed rewards, PhD Thesis, Cambridge University (1989)
White, R.W.: Motivation reconsidered: The concept of competece. Phychological Review 66, 297–333 (1959)
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Maher, M.L., Merrick, K., Macindoe, O. (2006). Intrinsically Motivated Intelligent Sensed Environments. In: Smith, I.F.C. (eds) Intelligent Computing in Engineering and Architecture. EG-ICE 2006. Lecture Notes in Computer Science(), vol 4200. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11888598_41
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DOI: https://doi.org/10.1007/11888598_41
Publisher Name: Springer, Berlin, Heidelberg
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