This approach might be useful to understand such phase transitions. Imagine the agents have a pairwise influence network that attract or repel one another, and further any subset of agents can be biased left or right as a function of time (like from a political convention), or to uncertain states (superposition).
https://science.sciencemag.org/content/361/6398/162 From: Friam <[email protected]> on behalf of Jochen Fromm <[email protected]> Reply-To: The Friday Morning Applied Complexity Coffee Group <[email protected]> Date: Saturday, June 6, 2020 at 12:27 PM To: The Friday Morning Applied Complexity Coffee Group <[email protected]> Subject: [FRIAM] Oblivion resistant swarm I would like to add an agent-based model for the last chapter of my book. The idea is to use a classic swarm as a model for a religious or political movement (since the basic rules like global attraction and local repulsion are isomorphic, as I argue in earlier chapters). The new thing is an "oblivion" factor which causes agents to forget the classic Boids swarm rules step by step. In order to keep the swarm from dissolving the model reinforces the rules every T timesteps, which simulates a rally, convention or congregation for the movement. Therefore the name "Oblivion Resistant Swarm" (ORS model) :-) As T varies, I expect to find some kind of phase transition in simulations where the swarm forms or dissolves. If T is too large, the swarm forgets the rules and is unable to maintain the form. If T is very small we get the classic Boids model and the swarm is able to form. Does that make any sense? Two more questions: 1. Is two weeks a reasonable timespan for the time we need to learn new rules in general? 2. Do you know any existing ABMs which are similar? -J.
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