Perspectives and challenges of agent-based simulation as a tool for economics and other social sciences

This paper argues that the agent-based simulation approach is just the one appropriate to the social sciences (including economics). Although there were many predecessor approaches, which tried to build formal models of social systems, all of them fell short of the peculiar features of the objects of all social sciences: complex systems consisting of numerous autonomous actors who interact with each other, who take on different roles at the same time, who are conscious of their interactions and roles and who can communicate with the help of symbolic languages even about the counterfactual. These human actors are unlike physical particles although their behaviour might sometimes be quite similar to the behaviour of physical particles when humans occur in very large numbers (but they are most interesting when they form only small networks). Real human actors would not concede that their behaviour is stochastic, they will always assert that their actions are deliberate (but at the same time these actions are not entirely predictable). Human actors are not entirely rational although their behaviour might sometimes seem as if they were (but they are most interesting when their rationality is only bounded and when their payoff is multidimensional). Social systems seem to be the most adaptive systems that we know about, and this is why we could perhaps use them as patterns for artificial adaptive systems — and if we knew enough about the modes of operations of human social systems, social sciences could even contribute to agent-based modelling in other fields.