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110 Socially Intelligent Agentsstudying applied problems do not regard data collection about social behaviouras an important part of the design process. Those interested in co-operatingrobots on a production line assess simulations in instrumental terms. Do theysolve the problem in a timely robust manner?The instrumental approach cannot be criticised provided it only does whatit claims to do: solve applied problems. Nonetheless, there is a question abouthow many meaningful problems are “really” applied in this sense. In practice,many simulations cannot solve a problem “by any means”, but have additionalconstraints placed on them by the fact that the real system interacts with, orincludes, humans. In this case, we cannot avoid considering how humans dothe task.Even in social science, some researchers, notably Doran [8] argue that therole of simulation is not to describe the social world but to explore the logicof theories, excluding ill-formed possibilities from discussion. For example,we might construct a simulation to compare two theories of social change inindustrial societies. Marxists assert that developing industrialism inevitablyworsens the conditions of the proletariat, so they are obliged to form a revolutionarymovement and overthrow the system. This theory can be comparedwith a liberal one in which democratic pressure by worker parties obliges thepowerful to make concessions. ½ Ignoring the practical difficulty of constructingsuch a simulation, its purpose in Doran’s view is not to describe how industrialsocieties actually change. Instead, it is to see whether such theories arecapable of being formalised into a simulation generating the right outcome:“simulated” revolution or accommodation. This is also instrumental simulation,with the pre-existing specification of the social theory, rather than actualsocial behaviour, as its “data”.Although such simulations are unassailable on their own terms, their relationshipwith data also suggests criticisms in a wider context. Firstly, is therejection of ill-formed theories likely to narrow the field of possibilities verymuch? Secondly, are existing theories sufficiently well focused and empiricallygrounded to provide useful “raw material” for this exercise? Should we justthrow away all the theories and start again?The second exception is that many of the most interesting social simulationsbased on MAS do make extensive use of data [1, 16]. Nonetheless, I think it isfair to say that these are “inspired by” data rather than based on it. From myown experience, the way a set of data gets turned into a simulation is somethingof a “dark art” [5]. Unfortunately, even simulation inspired by data is untypical.In practice, many simulations are based on agents with BDI architectures (forexample) not because empirical evidence suggests that people think like thisbut because the properties of the system are known and the programming ismanageable. This approach has unfortunate consequences since the designerhas to measure the parameters of the architecture. The BDI architecture might