Abstract
This chapter is meant to give a concise introduction to the topic of this book. The study of anticipatory behavior is referring to behavior that is dependent on predictions, expectations, or beliefs about future states. Hereby, behavior includes actual decision making, internal decision making, internal preparatory mechanisms, as well as learning. Despite several recent theoretical approaches on this topic, until now it remains unclear in which situations anticipatory behavior is useful or even mandatory to achieve competent behavior in adaptive learning systems. This book provides a collection of articles that investigate these questions. We provide an overview for all articles relating them to each other and highlighting their significance to anticipatory behavior research in general.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Adams, C., Dickinson, A.: Instrumental responding following reinforcer devaluation. Quarterly Journal of Experimental Psychology 33, 109–121 (1981)
Baluja, S., Pomerleau, D.A.: Expectation-based selective attention for visual monitoring and control of a robot vehicle. Robotics and Autonomous Systems 22, 329–344 (1997)
Bellman, R.: Dynamic programming. Princeton University Press, Princeton (1957)
Butz, M.V.: Anticipatory learning classifier systems. Kluwer Academic Publishers, Boston (2002)
Cañamero, L.D.: Modeling motivations and emotions as a basis for intelligent behavior. In: Johnson, W.L. (ed.) Proceedings of the first international symposium on autonomous agents (Agents 1997), New York, NY, pp. 148–155. The ACM Press, New York (1997)
Cañamero, L.D.: Designing emotions for activity selection in autonomous agents. In: Trappl, R., Petta, P., Payr, S. (eds.) Emotions in Humans and Artifacts. The MIT Press, Cambridge (2003) (in press)
Camacho, E.F., Bordons, C. (eds.): Model predictive control. Springer, Heidelberg (1999)
Carpenter, G.A., Grossberg, S., Reynolds, J.H.: ARTMAP: Supervised real-time learning and classification of nonstationary data by a self-organizing neural network. Neural Networks 4, 565–588 (1991)
Colwill, R.M., Rescorla, R.A.: Postconditioning devaluation of a reinforcer affects instrumental learning. Journal of Experimental Psychology: Animal Behavior Processes 11, 120–132 (1985)
Dubois, D.M.: Computing anticipatory systems with incursion and hyperincursion. In: Proceedings of the First International Conference on Computing Anticipatory Systems, CASYS-1997, pp. 3–30 (1998)
Gaudiano, P., Grossberg, S.: Vector associative maps: Unsupervised real-time error-based learning and control of movement trajectories. Neural Networks 4, 147–183 (1991)
Gérard, P., Sigaud, O.: YACS: Combining dynamic programming with generalization in classifier systems. In: Lanzi, P.L., Stolzmann, W., Wilson, S.W. (eds.) IWLCS 2000. LNCS (LNAI), vol. 1996, pp. 52–69. Springer, Heidelberg (2001)
von Glasersfeld, E.: Anticipations in the constructivist theory of cognition. In: Proceedings of the First International Conference on Computing Anticipatory Systems, CASYS-1997, pp. 38–48 (1998)
Hoffmann, J.: Vorhersage und Erkenntnis: Die Funktion von Antizipationen in der menschlichen Verhaltenssteuerung und Wahrnehmung. In: Anticipation and cognition: The function of anticipations in human behavioral control and perception, Hogrefe, Göttingen, Germany (1993)
Hommel, B.: Perceiving ones own action - and what it leads to. In: Jordan, J.S. (ed.) Systems theory and apriori aspects of perception, pp. 143–179. North Holland, Amsterdam (1998)
Kaelbling, L.P., Littman, M.L., Moore, A.W.: Reinforcement learning: A survey. Journal of Artificial Intelligence Research 4, 237–258 (1996)
Merriam-Webster. Merriam-webster online collegiate dictionary, 10th edn (2002), http://www.m-w.com/
Pashler, H., Johnston, J.C., Ruthruff, E.: Attention and performance. Annual Review of Psychology 52, 629–651 (2001)
Rescorla, R.A.: Associative relations in instrumental learning: The eighteenth Bartlett memorial lecture. Quarterly Journal of Experimental Psychology 43, 1–23 (1991)
Rosen, R.: Anticipatory systems. Pergamon Press, Oxford (1985)
Rosen, R.: Life itself. Columbia University Press, New York (1991)
Schubotz, R.I., von Cramon, D.Y.: Functional organization of the lateral premotor cortex. fMRI reveals different regions activated by anticipation of object properties, location and speed. Cognitive Brain Research 11, 97–112 (2001)
Sjölander, S.: Some cognitive break-throughs in the evolution of cognition and consciousness, and their impact on the biology language. Evolution and Cognition 1, 3–11 (1995)
Stolzmann, W.: Antizipative Classifier Systems [Anticipatory classifier systems]. Shaker Verlag, Aachen (1997)
Stolzmann, W.: Anticipatory classifier systems. In: Genetic Programming 1998: Proceedings of the Third Annual Conference, pp. 658–664 (1998)
Stolzmann, W.: An introduction to anticipatory classifier systems. In: Lanzi, P.L., Stolzmann, W., Wilson, S.W. (eds.) Learning classifier systems: From foundations to applications, pp. 175–194. Springer, Heidelberg (2000)
Sutton, R.S.: Reinforcement learning architectures for animats. In: From Animals to Animats: Proceedings of the First International Conference on Simulation of Adaptive Behavior, pp. 288–296 (1991)
Tani, J.: Model-based learning for mobile robot navigation from the dynamical systems perspective. IEEE Transactions. System, Man and Cybernetics (Part B) 26, 421–436 (1996) (special Issue on Learning Autonomous Systems)
Tolman, E.C.: Purposive behavior in animals and men. Appleton, New York (1932)
Tolman, E.C.: There is more than one kind of learning. Psychological Review 5b, 144–155 (1949)
Witkowski, C.M.: Schemes for learning and behaviour: A new expectancy model. PhD thesis, Department of Computer Science, Queen Mary Westfield College, University of London (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Butz, M.V., Sigaud, O., Gérard, P. (2003). Anticipatory Behavior: Exploiting Knowledge About the Future to Improve Current Behavior. In: Butz, M.V., Sigaud, O., Gérard, P. (eds) Anticipatory Behavior in Adaptive Learning Systems. Lecture Notes in Computer Science(), vol 2684. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45002-3_1
Download citation
DOI: https://doi.org/10.1007/978-3-540-45002-3_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40429-3
Online ISBN: 978-3-540-45002-3
eBook Packages: Springer Book Archive