The project was very short-lived, but (IIRC) the primary designer was Stafford Beer (https://en.wikipedia.org/wiki/Stafford_Beer) who based the work on his so-called Viable System Model (https://en.wikipedia.org/wiki/Viable_system_model). For the fundamental theories of the time you'd want to read Beer's works as well as those of his contemporaries, who espoused competing theories and methodologies. (I say "at the time" but the state of the art never really changed. Project Cybersyn is a fascinating chapter in the long-history of AI, and if there's any dominate thread to AI it's one of diminishing expectations and migration to ever more circumscribed problem domains.)
As I mention in my Amazon review the author, Eden Medina, seems to have compiled a ridiculous amount of material but only a fraction of it bleeds through into her book. The book is fascinating but if you're interested in the theory and history more generally then the book's bibliography is priceless.
It's been awhile since I read the book but here's one lasting impression: one of the biggest problems with Project Cybersyn was communication between producers and consumers. Much of the budget and time was actually spent on telecommunications infrastructure and then figuring out how to get people to use it properly. Which hints at one of the most important functions of a market: price signaling. Regardless of whether a market is efficient, given the dynamic nature of a complex economy any system you setup that tries to centralize price signaling (capturing pricing information is a prerequisite for processing it and generating optimal allocations) seems like it'd very quickly become antiquated and a hindrance. Markets may be inefficient but at scale not only are they remarkably powerful distributed computation engines, they co-evolve with the economy. But that doesn't mean there isn't room for applying these techniques in sub-domains (e.g. trading engines, city governance, etc), improving overall efficiency.
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