Eco-Logic: Logic-Based Approaches to Ecological Modelling

In the preface to the this book, the authors point out that simulation models can be useful tools for investigating real phenomena in an idealized way. However, the complexity of simulation models can often deter their use by ecologists. Also, complexity and implementation details of a simulation may obscure assumptions underlying the model. These observations provide partial justification for research carried out during 1984-1989 at the University of Edinburgh. This book contains a summary of that research. Two primary objectives for that work are 1) to provide tools for manipulating simulation models (i.e., implementation tools) and 2) to provide advice on conceptualizing real-world phenomena into an idealized representation for simulation (i.e., model design). Chapter 1 discusses modeling in very general terms. The authors specify three standards that they feel all simulation models should satisfy. These standards are based on the idea that a simulation model is essentially an argument proposed by the modeler about how some real-world system operates. They then show why conventional simulation models cannot meet those standards (i.e., those models are unable to explicitly characterize such an argument), especially in poorly understood subject areas. By “conventional,” the authors mean the direct implementation of a model in one of the imperative programming languages, such as FORTRAN, Pascal, or C. Alternatively, because a simulation model consists of assumptions (axioms) and rational arguments (inference methods), the authors reason that logic and logic programming can provide an excellent mechanism for representing and reasoning about simulation models. The primary focus of this book is on a logic-based approach to simulation modeling. Ecology was chosen as the experimental arena in which to apply these modeling ideas. In Chapter 2, the authors briefly introduce ecology and discuss some of the attributes that make it a complex and poorly understood science. They also present uses of ecological models, types of ecological models, and major modeling paradigms. Any new formalism for ecological modeling will have to take into account the diversity of these three areas. Prolog is introduced in Chapter 3 as one of the possible logic programming languages for the purposes of simulation modeling. The authors maintain that model comprehension is improved by logic because of its explicit structure, modularity, and flexibility of use. Three simple simulation models are constructed in Prolog to illustrate these points: 1) a system dynamics model, 2) a structural growth model, and 3) a state transition model. Also, the authors translate a conventional simulation model into Prolog. Without some prior experience with Prolog, it will be difficult for the reader to follow and understand these examples. The authors acknowledge this, and refer the reader to several introductory texts