a fascinating aspect of biological systems is how well they can be modeled using cellular automata; after all, multicellular organisms consist of (nearly) identical units reacting to adjacency-dependent environmental conditions in ways which generate emergent properties
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RT @ulkar_aghayeva
"How to understand cells, tissues and organisms as agents with agendas"
h/t @RogersBacon1
https://aeon.co/essays/how-to-understand-cells-ti…
https://twitter.com/ulkar_aghayeva/status/1444812107040575488
too little, and the agents cannot adequately synchronize on goals, and hence, align
too much and the agents cease to be distinct entities, which is likely suboptimal, as it lowers redundancy and parallelism
presumably related to the complexity of the relevant domain
the larger & more complex an agent is presumably the more bandwidth it requires to adequately align w/ another
I'd imagine this is proportional to the surface area of the agents informational boundary, as internal complexity increases w/ information flux
what's the growth rate?