Computational models of biological evolution have shown that both parochial and altruistic behaviors increase the fitness of the host by working in concert rather than on their own beneficial merits. The benefits of these mutually reinforcing behaviors include better resources management within an in-group through the elimination of out-groups. We present new models that allow for the evolution of parochial altruism in a robust computational system that show whether the biological benefits gained from these behaviors can find a correlate effect on fitness in a robust-first environment. Wide variation in resource availability within this computational system can give rise to “cooperative stalemates” among certain behavior categories. The new models display a dynamic interplay among these evolved behaviors as the populations compete for computational resources.
The paradigm of robust-first computing entails an infinitely scale-able environment in which elemental programs interact with each other to create emergent computational behaviors. The usefulness of such behaviors and the fitness of such elements can hold analogous properties to the system of biological evolution in the natural world. This paper will outline research that seeks to explore the evolution of parochial altruism in biological systems by modeling this behavior in a robust-first computational environment. We seek to determine whether the natural evolution of parochial altruism in the biological world, and the increased fitness that it brings, will find a correlate advantage to the elemental programs of robust-first computation, thereby increasing the overall fitness of those programs. We will create an elemental program that can take on one of four behavior categories: Parochial Altruists, Non-Parochial Altruists, Parochial Non-Altruists, and Non-Parochial Non-Altruists. We will allow these elements to interact with each other, both within an in-group of elements and other out-group elements, in a manner consistent with their behavior, and allow sexual reproduction that produces offspring programs with a genetic mix of the behavior patterns of both parents, subject to mutation, thereby modeling an evolutionary system. We will likewise be scaling a value of resource availability in the system from 10% - 50% of the occupied space to determine whether the presence or absence of abundant resources has a significant impact on the successful emergence of any one behavior category.
What we expect to find are the same results reached by the work of Choi and Bowles, wherein the prevalence of both Parochial Altruists and Non-Parochial Non-Altruists are significantly higher than that of just Altruists or just Parochials. That is, the emergence of each behavior serves to reinforce the other with a higher probability than either behavior flourishing alone. It is particularly expected that Non-Parochial Non-Altruists will have a propensity to emerge as a more ubiquitous trait category given the infinitely scale-able nature of the robust-first computation platform found in the Moveable Feast Machine. In other words, when there is little need to compete for resources, the groups that stay out of the fray will win out. Thus, as the resources are scaled up, the prevalence of NPNAs will be more commonplace, whereas when the resources are scaled down, the Parochial Altruists will be the more fit category within the system, based on the ability of PAs to harvest resources from other programs and eliminate them as a threat.