Emergence of glider-like structures in a modular robotic system

Information-driven evolutionary design has been proposed as an efficient method for designing self-organized multi-agent systems. Information transfer is known to be an important component of distributed computation in many complex systems, and indeed it has been suggested that maximization of information transfer can give rise to interesting behavior and induce necessary structure in a system. In this paper, we report the first known application of a direct measure of information transfer, transfer entropy, as a fitness function to evolve a self-organized multi-agent system. The system evolved here is a simulated snake-like modular robot. In the most fit snakebot in the final generation, we observe coherent traveling information transfer structures. These are analogous to gliders in cellular automata, which have been demonstrated to represent the coherent transfer of information across space and time, and play an important role in facilitating distributed computation. These observations provide evidence that using information transfer to drive evolutionary design can produce useful structure in the underlying system.