Temporal flocking and cacophony simulating agent communication in a noisy environment

Realistic communication is one of the most difficult aspects of simulating group behavior because the patterns produced by group communication are complex and not easily definable. In this paper, we present a model, developed using artificial life methodology, for creating simulations of group communication. Our model employs autonomous, artificial agents to produce emergent group behavior that resembles the communication patterns of a group, specifically, a flock of birds. Each agent collects information about its environment and its neighbors and follows a set of rules designed to meet both group goals and individual agent goals. Because we seek to establish emergent behavior, all behavioral decisions are made at the level of the individual agent, and there is no global control of the interaction among agents. Simulations using our model have successfully demonstrated agents issuing and heeding warning calls and have shown both the propagation of silence in response to a predator's presence and a return to a state of cacophony in a predator's absence. Eliciting these responses from the group involved introducing factors such as predators and a dominancy relationship into the synthetic world. This paper is part of the requirements for honors in computer science. The signatures below, by the advisor, a departmental reader, and a representative of the departmental honors committee, demonstrate that Jessica Crawford has met all the requirements needed to receive honors in computer science.