Chapter 5 . Applications of Adaptive Agents
87
available from lakes in the order of Tab. 2. I also want to thank Bernard Patten,
University of Georgia, U.S.A. for his critical but encouraging comments on the
first draft of the paper.
References
Bobbin J, Recknagel F (2001) Knowledge Discovery for Prediction and Explanation of
Blue-Green Aigal Dynamics in Lakes by Evolutionary Aigorithms. Ecol. Modelling
146, 1-3,253-264
Booth G (1997) Gecko: a continuos 2-D world for ecological modeling. Artif. Life 3, 147163
Forbes SA (1887) The lake as a microcosm. BuII.Sci.Ass., Peoria. Illinois, 77-87
Holland JH (1992) Adaptation in Natural and Artificial Systems. Addison-Wesley, New
York
Holland JH (1998) Emergence. From Chaos to Order. Oxford University Press, Oxford,
New York, Tokyo
Holland JH, Miller JH (1991) Artificial adaptive agents in economic theory. American
Economic Review 81, 2, 365-370
Huston M, DeAngelis D, Post W (1988) New computer models unify ecological theory.
BioScience 38, 10,682-691
Jorgensen SE, Mejer H (1979) A holistic approach to ecological modelling. Ecol.
Modelling 3, 39-61
Jorgensen SE (1986) Structural dynamics model. Ecol. Modelling 31, 1-9
Kaluzny S, Swartzman G (1985) Simulation experiments comparing alternative process
formulations using factorial design. Ecol.Modelling 28, 181-200
Kreft JU, Booth G, Wimpeny JWT (1998) BacSim, a simulator for individual-based
modelling ofbacterial colony growth. Microbiology 144,3275-3287
Lin F, Pai Y (2000) Using multi-agent simulation and learning to design new business
processes. IEEE Transactions on Systems, Man, and Cybernetics 30, 3, 380-384
Park RA, O'Neili RV, Bloomfield JA, Shugart HH, Booth RS, Goldstein RA, Mankin JB,
Koonce JF, Scavia D, Adams MS, Clesceri LS, Colon EM, Dettman EH, Hoopes JA,
Huff DD, Katz S, Kitchell JF, Koberger RC, La Row EJ, McNaught DC, Petersohn L,
Titus JE, Weiler PR, Wilkinson JW, Zahorcak CS (1974) A generalized model for
simulating lake ecosystems. Simulation 33-50
Radtke E, Straskraba M (1980) Self-optimization in a phytoplankton model. Ecol.
Modelling 9, 247-268
Railsback StF (2001) Concepts from complex adaptive systems as a framework for
individual-based modeling. Ecological Modelling 139,47-62
Recknagel F, Bobbin J, Whigham P, Wilson H (2002) Comparative application of artificial
neural networks and genetic algorithms for multivariate time series modelling of algal
blooms in freshwater lakes. Journal of Hydroinformatics 4, 2, 125-134
Recknagel F (1997) ANNA - Artificial Neural Network model predicting species
abundance and succession ofblue-green Algae. Hydrobiologia, 349,47-57
Recknagel F, French M, Harkonen P, Yabunaka K (1997) Artificial neural network
approach for modelling and prediction of algal blooms. Ecol. Modelling 96, 1-3, 11-28
87
available from lakes in the order of Tab. 2. I also want to thank Bernard Patten,
University of Georgia, U.S.A. for his critical but encouraging comments on the
first draft of the paper.
References
Bobbin J, Recknagel F (2001) Knowledge Discovery for Prediction and Explanation of
Blue-Green Aigal Dynamics in Lakes by Evolutionary Aigorithms. Ecol. Modelling
146, 1-3,253-264
Booth G (1997) Gecko: a continuos 2-D world for ecological modeling. Artif. Life 3, 147163
Forbes SA (1887) The lake as a microcosm. BuII.Sci.Ass., Peoria. Illinois, 77-87
Holland JH (1992) Adaptation in Natural and Artificial Systems. Addison-Wesley, New
York
Holland JH (1998) Emergence. From Chaos to Order. Oxford University Press, Oxford,
New York, Tokyo
Holland JH, Miller JH (1991) Artificial adaptive agents in economic theory. American
Economic Review 81, 2, 365-370
Huston M, DeAngelis D, Post W (1988) New computer models unify ecological theory.
BioScience 38, 10,682-691
Jorgensen SE, Mejer H (1979) A holistic approach to ecological modelling. Ecol.
Modelling 3, 39-61
Jorgensen SE (1986) Structural dynamics model. Ecol. Modelling 31, 1-9
Kaluzny S, Swartzman G (1985) Simulation experiments comparing alternative process
formulations using factorial design. Ecol.Modelling 28, 181-200
Kreft JU, Booth G, Wimpeny JWT (1998) BacSim, a simulator for individual-based
modelling ofbacterial colony growth. Microbiology 144,3275-3287
Lin F, Pai Y (2000) Using multi-agent simulation and learning to design new business
processes. IEEE Transactions on Systems, Man, and Cybernetics 30, 3, 380-384
Park RA, O'Neili RV, Bloomfield JA, Shugart HH, Booth RS, Goldstein RA, Mankin JB,
Koonce JF, Scavia D, Adams MS, Clesceri LS, Colon EM, Dettman EH, Hoopes JA,
Huff DD, Katz S, Kitchell JF, Koberger RC, La Row EJ, McNaught DC, Petersohn L,
Titus JE, Weiler PR, Wilkinson JW, Zahorcak CS (1974) A generalized model for
simulating lake ecosystems. Simulation 33-50
Radtke E, Straskraba M (1980) Self-optimization in a phytoplankton model. Ecol.
Modelling 9, 247-268
Railsback StF (2001) Concepts from complex adaptive systems as a framework for
individual-based modeling. Ecological Modelling 139,47-62
Recknagel F, Bobbin J, Whigham P, Wilson H (2002) Comparative application of artificial
neural networks and genetic algorithms for multivariate time series modelling of algal
blooms in freshwater lakes. Journal of Hydroinformatics 4, 2, 125-134
Recknagel F (1997) ANNA - Artificial Neural Network model predicting species
abundance and succession ofblue-green Algae. Hydrobiologia, 349,47-57
Recknagel F, French M, Harkonen P, Yabunaka K (1997) Artificial neural network
approach for modelling and prediction of algal blooms. Ecol. Modelling 96, 1-3, 11-28