Evolutionary Inversion of Swarm Emergence Using Disjunctive Combs Control

Given simple agent rules, a swarm's emergent behavior can be difficult to predict. The inverse problem is even more difficult: Given a desired emergent behavior, what are the rules by which swarm agents should operate? Disjunctive fuzzy control is proposed as a method to model swarm agents. Compared to more commonly used conjunctive fuzzy control such as that proposed by Mamdani, disjunctive fuzzy control is robustly fault tolerant and disjointly connected. Swarms are inherently disjunctive. Instead of agents working in coordination with one another, each swarm agent contributes individually to the result. The disjunctive attribute can also be applied at the sensor level for each individual agent. Disjunctive control allows adaptation of the describing membership function, as is commonly done in conjunctive control. The inversion process is illustrated with numerous simulation examples, including a predator-prey game, gang warfare, and escaping agents. The swarm is instructed what to do but not how to do it. Imposition of fitness constraints and repeated generations of evolutionary molding of agent performance can then result in unexpected emergent behaviors of the swarm, e.g., use of decoys, self-sacrifice, flanking maneuvers, and shielding of the weak.