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...
