https://en.wikipedia.org/wiki/Swarm_(simulation)
https://www.santafe.edu/research/results/working-papers/the-...
https://en.wikipedia.org/wiki/Swarm_(simulation)
https://www.santafe.edu/research/results/working-papers/the-...
Fun fact: Swarm was one of the very few non-NeXT/Apple uses of Objective C. We used the GNU Objective C runtime. Dynamic typing was a huge help for multiagent programming compared to C++'s static typing and lack of runtime introspection. (Again, nearly 30 years ago. Things are different now.)
I enjoyed using it around 2002, got introduced via Rick Riolo at the the University of Michigan Center for the Study of Complex Systems. It was a bit of a gateway drug for me from software into modeling, particularly since I was already doing OS X/Cocoa stuff in Objective-C.
A lot of scientific modelers start with differential equations, but coming from object-oriented software ABMs made a lot more sense to me, and learning both approaches in parallel was really helpful in thinking about scale, dimensionality, representation, etc. in the modeling process, as ODEs and complex ABMs—often pathologically complex—represent end points of a continuum.
Tangentially, in one of Rick's classes we read about perceptrons, and at one point the conversation turned to, hey, would it be possible to just dump all the text of the Internet into a neural net? And here we are.
C++ has added a ton of great features since (especially C++11 onward) but run-time reflection is still sorely missed.
https://youtube.com/playlist?list=PL6zSfYNSRHalAsgIjHHsttpYf...
The idea was to think about it from different directions including academia, industry, and education.
Nobody presented multi agent simulations but I agree with you that is a very interesting way of thinking about things. There was a talk on high dimensional systems modelled with networks but the speaker didn't want their talk published online.
Anyways I'm happy to chat more about these topics. I'm obsessed with understanding complexity using ai, modelling, and other methods.
> Nobody presented multi agent simulations but I agree with you that is a very interesting way of thinking about things.
To answer your question I did build a simulation of how a multi model agent swarm - agents have different capabilities and run times - would impact the end user wait time based on arbitrary message parsing graphs.
After playing with it for an afternoon I realized I was basically doing a very wasteful Markov chain enumeration algorithm and wrote one up accordingly.
As-is, it's hard to skim the playlist, and likely terrible for organic search on Google or YouTube <3