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Hello Sean, Tony, Claudio, Mike, thank you all for your answers, community = top notch :-)) * Claudio wrote: > you should consider MASON if you need: >-replicability guarantee >-computational and visualization separation for >-lots of runs (>103) without viz every run ;-) >-checkpointing for stats analysis >-evolutionary computational methods, as common for assessing learning. That is indeed exactly what I need. Especially visualization is very important, as I want to experiment with a few different approaches here. >We will make sure to send you the revised >paper as we develop it. Please do, I would be very glad, I've already printed the paper and am currently reading it :-) >Both Epstein and Axtell >(now at our Center, no longer Brookings) provided input. Wow. Cool! :-) I thoroughly enjoyed their Sugarscape book and it was a source of great inspiration. * Tony wrote >I'm just about to release my source code (refreshing it for MASON 11 >and doing general cleanup/commenting) and you'll be welcome to look at >or use it. I implemented 70-75% of the rules and outcomes in Growing >Artificial Societies. I'm looking forward to your code. >Any kind of complex cognitive architecture will fly against the >philosophy of Sugarscape, but is interesting that the agents have no >overt memory to use in reasoning/(ir)rational decision making. That is the big question - of course, the traditional CAS approach is to keep the individual components simple. But in the social simulation community voices have been raised (and I tend to concur - with reservations ;-) - that to make sensible descriptions of human societies one cannot completely neglect the cognitive aspect. I think one should iterete into more complex agents slowly, and see what happens. Generative science in the best sense ;-) > As agents/models become more complex they will >become more difficult to understand and in turn establishing causality >between code and simulation outcomes. Given the very little >replication that has occurred in this field, in general, there are many >open questions. That is quite true. I am just starting out with my Ph.D on this topic (cultural diffusion modeling), and I'm not yet sure where it will take me - more into the philosophy of science section, as in "how applicable are the results", "is generative science real science" etc; or into the design of cognitive agents useful for simulation; or a return to the simple agent and adjusting the interplay of agents. All exciting questions :-) One more thing: what I certainly intend to do is distribute the simulation in a second step (long term goal); if I use cognitive agents, there will be no other way to do simulation sensibly - does MASON lend itself easily to this? I know that you can add distributed support to Repast Models quite easily. Kind Regards and thank you for your responses, Günther P.S. >Alles gut >Claudio Danke :-)