[spam] my big issue is only being able to code a little at once, so planning the whole expansion of the algorithm is ideal. if it can write itself from one start, that's the best. unsure how doable that is. with what i have with me i'd probably need to handbuild its environment more than i'd like, which is still physically possible. i'm thinking of the structural aspects: belief tracking, communication, etc. what's really available is models. i've spent some time with mainstream neural networks, so that's what's easy for me to use nowadays. trying to work with others and not use too much of my brain :/ regarding models, how do these store things like beliefs, communication norms, etc? each part of the architecture could be a model, or it could be code. code doesn't adapt as well,but is clear and small. similarly, an architecture can be a single 'agent', or it can be multiple agents working together. when multiple ones work together, this gives them the possibility of discovering new architectures. discovering new architectures seems pretty helpful when the primary goal of the system is to craft general algorithms for engaging new systems. there are also freely available models that can generate source code. and the system could probably be tuned to have fixed source code.