Assessing Human Judgment of Computationally Generated Swarming Behavior - Harvey, John; Merrick, Kathryn Elizabeth; Abbass, Hussein A. (Frontiers in Robotics and AI, 2018)
Computer-based swarm systems, aiming to replicate the flocking behaviour of birds, were first introduced by Reynolds in 1987. In his initial work Reynolds noted that while it was difficult to quantify the dynamics of the behaviour from the model, observers of his model immediately recognised them as a representation of a natural flock. Considerable analysis has been conducted since then on quantifying the dynamics of flocking/swarming behaviour. However, no systematic analysis has been conducted on human identification of swarming. In this paper we assess subjects' assessment of the behaviour of a simplified version of Reynolds' model. Factors that affect the identification of swarming are discussed and future applications of the resulting models are proposed. Differences in decision times for swarming-related questions asked during the study indicate that different brain mechanisms may be involved in different elements of the behaviour assessment task. The relatively simple, but finely tuneable model used in this study provides a useful methodology for assessing individual human judgement of swarming behaviour.