Frequented Paths of Genetically Evolved Neural Networks is a series of images tracing the paths of artificially intelligent autonomous agents as they move around a simulated environment. The actions of each agent is defined by an evolved neural network, unique to that agent. This process of neuroevolution favors the agents whose neural network allows them to find, and remain near, a source of energy in the center of the environment. Though the initial conditions of each simulation are randomized, common behavioral patterns emerge from the chaos.