Abstract:
This investigation aims to arrive at a minimal working model of an agent whose
central controller comprises an artificial chemical network. The agent possesses two
wheels to navigate within a spatiotemporal environment containing finite resources
that are necessary for the system to sustain itself. To this end, a genetic algorithm is
employed and chemical networks are evolved successfully in simulation. The emergent
behaviours are analysed and demonstrate learned associations for action selection.