I found a description of this in several books about artificial intelligence for game developers [e.g. Buckland (2006) Programming Game AI by Example - Chapter 2; Bourg and Seemann (2004) AI for Game Developers - Chapter 9] and was wondering if anyone had applied this approach to program Social Simulations or Management Science Simulations (without using secondary software like Swarm or Repast)? Would you be willing to share your code?
Hi, in fact I have a question. What do you mean by "Finite State Machines" ? This term is usually used to describe the less powerful in the hierarchy of virtual machines, since they have a finite number of states. They are usually used to analyze language, or syntax (compilers)...Agent-based models usually do not match with the kind of object FSMs are applied on. May be there is a certain convergence with cellular automata which have been widely used in ecology and social sciences (see for instance NetLogo software which use a grid for space). But the formers have been advantageously replaced by simulators mixing analytic and stochastic components discrete in time but continuous in space, so that the number of states of agents is not known and undefined (except if you decide it).
Sorry for keeping you waiting for a year - just spotted your answer a minute ago. I often have similar discussions with members of our Functional Programming Research Group. As far as I understand the term "Finite State Machines" is used for different things in different contexts (theoretical computer science vs. applied computer science).
We have now published a conference paper in response to our earlier question. In this paper we have tried to clarify this issue and present the different perspectives. I would be very interested to hear from you if we succeeded :).
https://fedcsis.org/proceedings/2014/pliks/335.pdf
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