A reactively learning neural network that decides behaviours for an artificial life system with homogeneous agents

Creating a system that can accurately reflect life like decision making for survival purposes is no small task. To do so we must look to explain the behavioral patterns of life, which is a topic that is huge in scope and inordinately complex. Some help to approach this problem can be found in evolutionary mechanisms, previous works on artificial life and behavioral psychology. From here we can begin to form an idea of how biological organisms perpetuate their existence and how one might go about re-creating elements of these mechanisms artificially. This paper describes a system created to explore this idea.