A part of complexity science that deals directly with nature-inspired evolutionary processes involving interaction in the fitness function. A definition I've used in the past is that these algorithms involve an evolutionary dynamics in which one or more types of agent playing two or more distinct roles interact with measureable outcomes that impact the agents' future evolution. interactive domains are one possible precise formulation of the underlying data needed. Because there is an evolutionary dynamics at work, the algorithm has a state consisting either of one or more populations or one or more distributions over agents.
Through my PhD dissertation work I came to understand that the mechanism by which that impact is realized is that interactions function as measurements, and how any two agents compare can change fundamentally (e.g., change order) depends on the interactions in which they participate. I developed a way of capturing that information in what I termed coordinate systems, a notion that led to DECA as a published algorithm.