Applying artificial intelligence techniques to ecological modeling

Abstract The field of artificial intelligence has recently been having noticeable success in such fields as natural-language processing, expert systems, and equation solving. The time is right for applying these techniques to simulation. Ecological simulation could benefit from these techniques because ecosystem models are complex, ill-defined, and error-prone, and span a spectrum of mathematical formalisms. Expert system technologies could allow incorporation of domain-specific knowledge and organism or management behavior rules. Symbolic manipulation allows checking for errors by use of methods such as balanced units and conservation of energy. It could also simplify manipulation of equations and model alteration. A variety of new analysis and manipulation tools could become available to ecological modelers if artificial intelligence techniques were applied.

[1]  Eric Rexstad,et al.  Model simplification — Three applications , 1985 .

[2]  B. Sheil.  Power tools for programmers , 1986 .

[3]  R. May,et al.  Stability and Complexity in Model Ecosystems , 1976, IEEE Transactions on Systems, Man, and Cybernetics.

[4]  Gordon S. Novak.  Representations of Knowledge in a Program for Solving Physics Problems , 1977, IJCAI.

[5]  Herbert A. Simon,et al.  Understanding written problem instructions. , 1974 .

[6]  Donald L. DeAngelis,et al.  Criteria that forbid a large, nonlinear food-web model from having more than one equilibrium point , 1978 .

[7]  Edward H. Shortliffe,et al.  Computer-based medical consultations, MYCIN , 1976 .

[8]  S. Rinaldi,et al.  Stability analysis of predator-prey models via the Liapunov method. , 1977 .

[9]  Stephen H. Levine,et al.  Several measures of trophic structure applicable to complex food webs , 1980 .

[10]  Ronald N. Kickert.  Names of published computer models in the environmental biological sciences: A partial list and new potential risks , 1984 .

[11]  N. Nie.  SPSS-X User's Guide , 1983 .

[12]  Robert S. Engelmore,et al.  SACON: A Knowledge-Based Consultant for Structural Analysis , 1979, IJCAI.

[13]  Stephen P. Kaluzny,et al.  Simulation experiments comparing alternative process formulations using a factorial design , 1985 .

[14]  George S. Innis,et al.  Simulation model simplification techniques , 1983 .

[15]  Craig Leohle,et al.  Evaluation of theories and calculation tools in ecology , 1983 .

[16]  Sitansu S. Mittra.  Discrete system simulation concepts , 1984 .

[17]  Paul A. Luker.  Modeller: Computer-assisted modelling of continuous systems , 1984 .

[18]  P. Auger.  Hierarchically organized populations: interactions between individual, population, and ecosystem levels , 1983 .

[19]  H. de Swaan Arons.  Expert systems in the simulation domain , 1983 .

[20]  Bruce G. Buchanan,et al.  On generality and problem solving: a case study using the DENDRAL program , 1970 .

[21]  Robert V. O'Neill,et al.  A comparison of sensitivity analysis and error analysis based on a stream ecosystem model , 1981 .

[22]  Albert T. Corbett,et al.  Intelligent Tutoring Systems , 1985, Science.

[23]  Philip Klahr.  ARTIFICIAL INTELLIGENCE APPROACHES TO SIMULATION , 1984 .

[24]  W. Schaffer.  ECOLOGICAL ABSTRACTION: THE CONSEQUENCES OF REDUCED DIMENSIONALITY IN ECOLOGICAL MODELS' , 1981 .

[25]  Georgios I. Doukidis,et al.  Research into Expert Systems to Aid Simulation Model Formulation , 1985 .

[26]  Sze-Bi Hsu.  The application of the Poincaré-transform to the Lotka-Volterra model , 1978 .

[27]  W. D. Valentine,et al.  The concepts of elasticity, invulnerability and invadability. , 1979, Journal of theoretical biology.

[28]  P. M. Nanninga,et al.  Developing a fire management expert system for Kakadu National Park, Australia , 1986 .

[29]  Robert M. O'Keefe,et al.  Simulation and expert systems- A taxonomy and some examples , 1986 .

[30]  Efraim Halfon,et al.  Is there a best model structure? I. Modeling the fate of a toxic substance in a lake , 1983 .

[31]  G. C. Vansteenkiste,et al.  The impact of advanced information processing on simulation — An illustrative review , 1986 .

[32]  H Lemmon,et al.  Comax: An Expert System for Cotton Crop Management , 1986, Science.

[33]  Shripad Tuljapurkar,et al.  Stochastic instability and Liapunov stability , 1979 .

[34]  T. Gard,et al.  Top predator persistence in differential equation models of food chains: The effects of omnivory and external forcing of lower trophic levels , 1982, Journal of mathematical biology.

[35]  M. Gilpin,et al.  Multiple domains of attraction in competition communities , 1976, Nature.

[36]  Sector stability of a complex ecosystem model , 1978 .

[37]  B. W. Rust,et al.  Interactive modeling of ecosystems , 1974 .

[38]  D G Bobrow,et al.  Perspectives on Artificial Intelligence Programming , 1986, Science.

[39]  R. P. Canale,et al.  Comparison of first‐order error analysis and Monte Carlo Simulation in time‐dependent lake eutrophication models , 1981 .

[40]  Thomas C. Gard.  Persistence in stochastic food web models , 1984 .

[41]  Heimo H. Adelsberger,et al.  Expert systems and simulation , 1985 .