If the new topic you want to learn is “extended behavior networks”, then maybe this is your best bet. But if you really want to learn about something like AI or ML or the design of agents that behave reasonably by the standards of some utility-like theory, then this is probably a bad choice. A quick search in Google Scholar (if you’re not using this, or some equivalent, making this a step before going to the hivemind is a good idea) suggests that extended behavior networks are backwater-y. If the idea of a network of things interacting to make a decision appeals to you, maybe look into Petri nets or POMDPs. Or better yet, start with something like Russel and Norvig’s AIMA to get a better view of the landscape. If the irrationality part is interesting, start with Kahneman, Slovic, and Tversky’s Judgment under uncertainty: Heuristics and biases, which gives you a curated collection of jargoney papers.
Seconding a lot of calef’s observations.
If the new topic you want to learn is “extended behavior networks”, then maybe this is your best bet. But if you really want to learn about something like AI or ML or the design of agents that behave reasonably by the standards of some utility-like theory, then this is probably a bad choice. A quick search in Google Scholar (if you’re not using this, or some equivalent, making this a step before going to the hivemind is a good idea) suggests that extended behavior networks are backwater-y. If the idea of a network of things interacting to make a decision appeals to you, maybe look into Petri nets or POMDPs. Or better yet, start with something like Russel and Norvig’s AIMA to get a better view of the landscape. If the irrationality part is interesting, start with Kahneman, Slovic, and Tversky’s Judgment under uncertainty: Heuristics and biases, which gives you a curated collection of jargoney papers.