This paper discusses partial results of an ongoing project focused on analysing the current usefulness and implications of developing research on agent-based social simulation models beyond academic, hobbyist or educational purposes. Design, development and testing phases of such modelling are discussed along with common issues evidence-driven modellers often face whilst collecting, analysing and modelling quantitative and qualitative data into social simulations. It also includes a discussion on the evidence gathered in published literature and structured interviews with researchers that have lead (...) mid- to long-term (3–5 years) projects on social simulation in Europe and the United States. Finally, good-practice recommendations are put forward by presenting a development methodology fully guided by evidence. (shrink)

The literature in agent-based social simulation suggests that a model is validated when it is shown to ‘successfully’, ‘adequately’ or ‘satisfactorily’ represent the target phenomenon. The notion of ‘successful’, ‘adequate’ or ‘satisfactory’ representation, however, is both underspecified and difficult to generalise, in part, because practitioners use a multiplicity of criteria to judge representation, some of which are not entirely dependent on the testing of a computational model during validation processes. This article argues that practitioners should address social epistemology to achieve (...) a deeper understanding of how warrants for belief in the adequacy of representation are produced. Two fundamental social processes for validation: interpretation and commensuration, are discussed to justify this claim. The analysis is advanced with a twofold aim. First, it shows that the conceptualisation of validation could greatly benefit from incorporating elements of social epistemology, for the criteria used to judge adequacy of representation are influenced by the social, cognitive and physical organisation of social simulation. Second, it evidences that standardisation tools such as protocols and frameworks fall short in accounting for key elements of social epistemology that affect different instances of validation processes. (shrink)

Even though the philosophy of simulation is intended as a comprehensive reflection about the practice of computer simulation in contemporary science, its output has been disproportionately shaped by research on equation-based simulation in the physical and climate sciences. Hence, the particularities of alternative practices of computer simulation in other scientific domains are not sufficiently accounted for in the current philosophy of simulation literature. This article centres on agent-based social simulation, a relatively established type of simulation in the social sciences, to (...) exemplify this claim. The analysis advanced has a twofold goal. First, it shows that the philosophy of agent-based social simulation, mostly developed by practitioners themselves, is, on one hand, heavily influenced by the methodological features of agent-based modelling and by the loose and fragmented character of social theory and, on the other hand, distinctively shaped by contrasting views of what it implies to do social research with virtual or artificial societies. Second, it suggests ways in which cross-fertilisation could enrich the philosophical understanding of computer simulation both in agent-based social simulation and in the philosophy of simulation. (shrink)

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. (shrink)

This paper presents a evolutionary simulation where the presence of 'tags' and an inbuilt specialisation in terms of skills result in the development of 'symbiotic' sharing within groups of individuals with similar tags. It is shown that the greater the number of possible sharing occasions there are the higher the population that is able to be sustained using the same level of resources. The 'life-cycle' of a particular cluster of tag-groups is illustrated showing: the establishment of sharing; a focusing-in of (...) the cluster; the exploitation of the group by a particular skill-group and the waning of the group. This simulation differs from other tag-based models in that is does not rely on either the forced donation of resources to individuals with the same tag and where the tolerance mechanism plays a significant part. These 'symbiotic' groups could provide the structure necessary for the true emergence of artificial societies, supporting a division of labour similar to that found in human societies. (shrink)

All tools have their advantages and disadvantages and for all tools there are times when they are appropriate and times when they are not. Formal tools are no exception to this and systems of numbers are examples of such formal tools. Thus there will be occasions where using a number to represent something is helpful and times where it is not. To use a tool well one needs to understand that tool and, in particular, when it may be inadvisable to (...) use it and what its weaknesses are. However we are in an age that it obsessed by numbers. Governments spend large amounts of money training its citizens in how to use numbers and their declarative abstractions (graphs, algebra etc.) We are surrounded by numbers every day in: the news, whether forecasts, our speedometers and our bank balance. We are used to using numbers in loose, almost “conversational” ways – as with such concepts as the rate of inflation and our own “IQ”. Numbers have become so famliar that we no more worry about when and why we use them than we do about natural language. We have lost the warning bells in our head that remind us that we may be using numbers inappropriately. They have entered (and sometimes dominate) our language of thought. Computers have exasperbated this trend by making numbers very much easier to store/manipulate/communicate and more seductive by making possible attractive pictures and animations of their patterns. More subtley, when thought of as calculating machines that can play games with us and simulate the detail of physical systems, they suggest that everything comes down to numbers. For this reason it is second nature for us to use numbers in our social simulations and we frequently do so without considering the consequences of this choice. This paper is simply a reminder about numbers: a call to remember that they are just another (formal) tool; it recaps some of the conditions which indicate when a number is applicable and when it might be misleading; it looks at some of the dangers and pitfalls of using numbers; it considers some examples of the use of numbers; and it points out that we now have some viable alternatives to numbers that are not any less formal but which may be often preferable. (shrink)

The terms ‘verification’ and ‘validation’ are widely used in science, both in the natural and the social sciences. They are extensively used in simulation, often associated with the need to evaluate models in different stages of the simulation development process. Frequently, terminological ambiguities arise when researchers conflate, along the simulation development process, the technical meanings of both terms with other meanings found in the philosophy of science and the social sciences. This article considers the problem of verification and validation in (...) social science simulation along five perspectives: The reasons to address terminological issues in simulation; the meaning of the terms in the philosophical sense of the problem of “truth”; the observation that some debates about these terms in simulation are inadvertently more terminological than epistemological; the meaning of the terms in the technical context of the simulation development process; and finally, a comprehensive outline of the relation between terminology used in simulation, different types of models used in the development process and different epistemological perspectives. (shrink)

We consider here issues of open access to social simulations, with a particular focus on software licences, though also briefly discussing documentation and archiving. Without any specific software licence, the default arrangements are stipulated by the Berne Convention (for those countries adopting it), and are unsuitable for software to be used as part of the scientific process (i.e. simulation software used to generate conclusions that are to be considered part of the scientific domain of discourse). Without stipulating any specific software (...) licence, we suggest rights that should be provided by any candidate licence for social simulation software, and provide in an appendix an evaluation of some popularly used licences against these criteria. (shrink)