Abstract
The various modifications and extensions of the anticipatory classifier system (ACS) recently led to the introduction of ACS2, an enhanced and modified version of ACS. This chapter provides an overview over the system including all parameters as well as framework, structure, and environmental interaction. Moreover, a precise description of all algorithms in ACS2 is provided.
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References
Butz, M.V. (2001a). Anticipatory learning classifier systems. Genetic Algorithms and Evolutionary Computation. Boston, MA: Kluwer Academic Publishers.
Butz, M.V. (2001b). An implementation of the anticipatory classifier system ACS2 in C++ (IlliGAL report 2001026). University of Illinois at Urbana-Champaign: Illinois Genetic Algorithms Laboratory, http://www-illigal.ge.uiuc.edu/sourcecd.html.
Butz, M.V. (2002). Biasing exploration in an anticipatory learning classifier system. In Lanzi, P. L., Stolzmann, W., and Wilson, S. W. (Eds.), Proceedings of the Fourth International Workshop on Learning Classifier Systems (IWLCS-2001) Berlin Heidelberg: Springer-Verlag.
Butz, M.V., Goldberg, D.E., and Stolzmann, W. (2000). Introducing a genetic generalization pressure to the anticipatory classifier system: Part 1-theoretical approach. In Whitely, D., Goldberg, D.E., Cantu-Paz, E., Spector, L., Parmee, I., and Beyer, H.-G. (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2000) pp. 34–41. San Francisco, CA: Morgan Kaufmann.
Butz, M.V., Goldberg, D.E., and Stolzmann, W. (2001). Probability-enhanced predictions in the anticipatory classifier system. In Lanzi, P.L., Stolzmann, W., and Wilson, S.W. (Eds.), Advances in Learning Classifier Systems, LNAI 1996 pp. 37–51. Berlin Heidelberg: Springer-Verlag.
Dorigo, M., and Colombetti, M. (1997). Robot Shaping, an experiment in behavior engineering. Intelligent Robotics and Autonomous Agents. Cambridge, MA: MIT Press.
Lanzi, P.L. (2000). Learning classifier systems from a reinforcement learning perspective (Technical Report 00-03). Dipartimento di Elettronica e Informazione, Politecnico di Milano.
Stolzmann, W. (1997). Antizipative Classifier Systems [Anticipatory classifier systems]. Aachen, Germany: Shaker Verlag.
Stolzmann, W. (1998). Anticipatory classifier systems. In Koza, J.R., Banzhaf, W., Chellapilla, K., Deb, K., Dorigo, M., Fogel, D., Grazon, M., Goldberg, D., Iba, H., and Riolo, R. (Eds.), Genetic Programming 1998: Proceedings of the Third Annual Conference pp. 658–664. San Francisco, CA: Morgan Kaufmann.
Stolzmann, W., Butz, M. V., Hoffmann, J., and Goldberg, D. E. (2000). First cognitive capabilities in the anticipatory classifier system. In Meyer, J.-A., Berthoz, A., Floreano, D., Roitblat, H., and Wilson, S. W. (Eds.), From Animals to Animats 6: Proceedings of the Sixth International Conference on Simulation of Adaptive Behavior pp. 287–296. Cambridge, MA: MIT Press.
Watkins, C.J.C.H. (1989). Learning from delayed rewards. Doctoral dissertation, King’s College, Cambridge, UK.
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Butz, M.V., Stolzmann, W. (2002). An Algorithmic Description of ACS2. In: Lanzi, P.L., Stolzmann, W., Wilson, S.W. (eds) Advances in Learning Classifier Systems. IWLCS 2001. Lecture Notes in Computer Science(), vol 2321. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48104-4_13
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DOI: https://doi.org/10.1007/3-540-48104-4_13
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