Understanding the concepts behind flocks and crowds

As with previous concepts, it's easiest to understand flocks and herds by relating them to the real-life behaviors they model. As simple as it sounds, these concepts describe a group of objects, or boids as they are called in artificial intelligence lingo, moving together as a group. The flocking algorithm gets its name from the behavior birds exhibit in nature, where a group of birds follow one another toward a common destination, mostly keeping a fixed distance from each other. The emphasis here is on the group. We've explored how single agents can move and make decisions on their own, but flocks are a relatively computationally efficient way of simulating large groups of agents moving in unison while modeling unique movement in each boid that doesn't rely on randomness or predefined paths.

The implementation that we'll be building in this chapter for flocking is built upon the concepts originally developed by Craig Reynolds himself. There...