(309f) Emergence of Spontaneous Order in the Dynamics of Birds Flocking: A Statistical Teleodynamics Perspective

The physics of active matter, such as bacterial colonies and bird flocks, exhibiting interesting self-organizing dynamical behavior has gained considerable importance in recent years. Recent theoretical advances use techniques from hydrodynamics, kinetic theory, and non-equilibrium statistical physics. However, for biological agents, these don't seem to recognize explicitly their critical feature, namely, the role of survival-driven purpose and hence the pursuit of increasing utility. In this presentation, we describe a novel framework, called statistical teleodynamics, that addresses this challenge.

In the dynamics of birds flocking, Reynolds’s model has been used extensively to simulate the collective behavior. The model is a set of velocity update rules of motion of bird-like entities (boids) where each agent changes its direction of motion based on its neighboring birds. However, there is an “inherent goal“ in the motion of these agents that is not apparent from the simple velocity update rules.

In this work, we view the flocking of birds as a result of the goal-driven behavior of the birds. We show how the flocking phenomenon is actually a result of agents trying to increase their utility, which is dependent on the relative position and alignments of their neighbors. In doing so, we notice the similarity between the update rules as seen in the Reynolds’s model and the utility-driven model. We show a surprising result that the bird-like agents (boids) self-organize dynamically into flocks to reach an arbitrage equilibrium of equal effective utilities for all boids. While it has been well-known for three centuries that there are constants of motion for passive matter, it comes as a surprise to discover that the dynamics of active matter populations could also have an invariant. What we demonstrate is for ideal systems, similar to the ideal gas or Ising model in thermodynamics. The next steps would involve examining and learning how real swarms behave compared to their ideal versions. Our theory is not limited to just birds flocking but applicable to the self-organizing dynamics of other active matter systems.