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6.8 Representation of the model in Prolog
Prolog ("Programming in logic") is a computer language that was developed for representing and
reasoning with statements in a particular form of logic, called 'first-order predicate logic'. It
represents an approach to computer programming that is totally different from that of most
computer languages. In Prolog, a computer program consists of a collection of statements, which
are taken to be true statements about some subset of the world. These statements can either be
facts (rabbits eat grass) or rules (X is a herbivore if X eats grass). An introduction to Prolog is
given in Appendix A2.
Why is this relevant to declarative modelling? First, declarative modelling involves making lots
of factual statements about a model: "The model contains a compartment called biomass and a
flow called photosynthesis", for example. Prolog provides a compact way of capturing these
statements. Second, a lot of the work we do as modellers involves reasoning about models:
following influence chains through the model, interrogating the model structure, or finding models
with certain properties. Some of these operations can be done in XSLT, but Prolog rules provide
a far more powerful mechanism for doing this type of reasoning with models. Prolog is thus an
ideal language for representing models declaratively (as a set of facts), and also for reasoning with
models so represented. Muetzelfeldt et al (1989) discuss the utility of Prolog for ecological
modelling; Robertson et al (1991) report on research into the representation of ecological models
as logical statements in Prolog; and McIntosh et al (2003) presents a rule-based model,
implemented in Prolog, for vegetation dynamics.
Box 6.6 shows one way of representing the grass/water model in Prolog, using System Dynamics
concepts.
Box 6.6 The grass/water model represented in Prolog
compartment(grass, 10).
compartment(water, 20).
flow(growth, outside, grass, 0.01*grass*water).
flow(rain, outside, water, 10).
flow(transpiration, water, outside, 0.02*grass*water).
We state here that the model has 2 compartments and 3 flows. The 'compartment' predicate has
two arguments, representing the compartment name and its initial value. The 'flow' predicate has
4 arguments, representing the flow name, the source and destination compartments for the flow,
and the equation used for calculating its value. Note the close similarity to the relational database
representation: in fact, Prolog can be considered as a relational language.
Prolog can be used for interrogating and reporting on model structure, in much the same way as
using XML and XSLT, or the model in an Access database. However, the real power of Prolog
comes when we want to do some form of reasoning with the model design, going beyond
interrogation or reporting. For example, we might want to:
• trace through influence or flow networks, for example finding all flows directly or indirectly
influenced by a certain parameter, or all compartments on a particular flow network;
• check model syntax, i.e. that the model design adheres to rules of System Dynamics (e.g. no
flows pointing to variables);
• generate a C++ program from the model representation - this is exactly what Simile does when
you want to run a model;
• transform a model - e.g. collapse a complex part of the model into something simpler
(Muetzelfeldt and Yanai, 1996);
• automatically compare two models - perhaps each derived from a parent model by two
separate groups over a 6-month period.
Such tasks can also be programmed in other languages, but Prolog is especially suited for it: it is a
symbolic reasoning language, and thus ideal for reasoning with a symbolically-represented model.