Formidable difficulties face anyone trying to model social phenomena using a formal system, such as a computer program. The differences between formal systems and complex, multi-facetted and meaning-laden social systems are so fundamental that many will criticise any attempt to bridge this gap. Despite this, there are those who are so bullish about the project of social simulation that they appear to believe that simple computer models, that are also useful and reliable indicators of how aspects of society works, are not only possible but within our grasp. This paper seeks to pour water on such optimism but, on the other hand, show that useful computational models might be 'evolved'. In this way it is disagreeing with both naive positivist and relativistic post-modernist positions. However this will require a greater 'selective pressure' against models that are not grounded in evidence, 'floating models', and will result in a plethora of complex and context-specific models. This paper takes a naturalistic and evolutionary view of science following such as (Toulmin 1967 , Toulmin 1972 , Popper 1972 , Campbell 1974 , and Hull 1988 . However it differs from them as it does not claim an evolution of knowledge or ideas in the abstract, but rather an evolution of formal models (in this case social simulation models). I will not refer to this extensive literature since although close to what is being discussed below, is subtly oblique to it -I think the arguments will be clearer without that complication. This is a synthesis and development of many of my previous papers, especially (Edmonds 2000) , so I apologise in advance for the number of self-citations. There are many difficulties facing the social scientist who wants to capture some aspects of observed social phenomena in a simulation model. Firstly, there is the sheer difference between the formal models (i.e. computer programs) that we are using as compared to the social world that we observe. The former are explicit, precise, with a formal grammar, predictable at the micro-level, reproducible and work in the same way (pretty well) regardless of the computational context. The later are vague, fluid, uncertain, flaky, implicit and imprecise -which often seems to work completely different in similar situations, and whose operation seems to rely on the rich interaction of meaning in a way that is sometimes explicable but almost never predictable. In particular the gap between essentially formal symbols with 'thin' meaning and the rich semantic associations of the observed social world (for example as expressed in natural language) is particularly stark. A gap so wide that some philosophers have declared it unbridgeable (e.g. Lincoln and Guba 1985) .
Edmonds REF addresses simulation models that are similar to the generated data model we use for our analysis.
Bootstrapping Knowledge about Social Phenomena using Simulation Models
ICALT
Psychology Computer Science