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=====The Evolution of Parochial Altruism in Scarcity Systems=====


====Introduction====

Parochial Altruism is the interplay between altruism towards ones own tribe, and hostility towards outside groups ((Choi, Jung-Kyoo, & Bowles, Samuel (2007). The Coevolution of Parochial Altruism and War.
Science 26 October 2007: Vol. 318 no. 5850 pp. 636-640 DOI: 10.1126/science.1144237)). Individually, the act of either altruism or parochialism and the benefits thereof are weighed against the cost of such an act. In other words, the decision to engage in either one depends on whether it is more beneficial to not do it. From an evolutionary perspective, this is a weak mechanism for suitability in the gene pool. However both acts engaged in as a reinforcement to the other would make for a much stronger viability in the long term, and help ensure the persistence and evolution of both. 

My project seeks to test this theory by creating a set of tribes of individuals who are given a choice whether to help their own tribe or not, as well as whether to attack an outsider or not. Based on the theory, we should see the growth and persistence of both behaviors more often than only one surviving in the population. Likewise, I would like to see how well this system behaves under various states of scarcity, and what effect that might have on a groups decision to be altruistic, hostile, or some combination thereof.

{{ :people:chris_symonds:f1.large.jpg?nolink&300 |Between-Group Interaction}}

====Elements====

For this simulation, I will make use of Dregs and Res, both to serve as "Random tragedy" that might strike an arbitrary denizen of the simulation, and as resources that must be gathered and used by the fauna, respectively.\\ \\
The new element that would be needed is the agent itself. The agent would be assigned a group and an initial genetic makeup that allows for some probability of altruism and another independent probability towards hostility. Setting a threshold value for each, the traversal of which would categorize the being into an overall binary state, gives rise to four distinct types within the system:\\ 
  * Parochial Altruists
    * The general behavior of a Parochial Altruist will be to have some probability of attacking the Parochial members of an out-group, and retains any direct benefit gained from that conflict. The benefit to the in-group is a reduction in threat from out-groups.
  * Parochial Non-Altruists
    * Parochial Non-Altruists will attempt to steal resources from out-groups at reduced risk and reward. They will not share resources with the in-group.
  * Non-Parochial Altruists
    * May share resources with in-group members. There is also a small chance that they will share resources with certain out-group members which may convert that member to the sharer's group.
  * Non-Parochial Non-Altruists
    * Will abstain from sharing with or attacking any group.

Depending on the capabilities of the MFM and my ability to track global information from each agent, it might be necessary to make each type an element unto itself, each with identical behaviors, to help ascertain type proportions within a given population.

Individuals of an in-group will be allowed to procreate if they happen to encounter each other and have sufficient resources, passing on some random combination of their genetic makeup to their offspring, allowing the dominance of whatever behavior will naturally arise.

====Simulation====

The simulation runs will consist of various settings to the number of groups (k), the number of agents per group (n), the DREG probability for producing RES, and the individual tuning of the agents themselves and the various probabilities within their behaviors. Simulations will be run for a consistent number of kAEPS across all setting combinations, or until all agents have perished, whichever comes first.

The overall actions of an agent will be conducted in the following manner:

  - Look in each direction and ascertain the neighborhood.
  - If a RES is available, consume the RES.
  - Conduct any genetic-driven business
    - PA: Attack any single out-group Ps in the neighborhood.
    - PNA: Attempt to steal from the least-threatening out-group agent in the neighborhood.
    - NPA: Evaluate the needs of each agent in the neighborhood and share based on cost/benefit
    - NPNA: Do a little dance.
  - Reproduce
    - If multiple potential mates exist within the neighborhood, choose uniformly at random
    - ????
    - Offspring will appear in any available location within the event window. If no such free location is available, the reproduction is canceled and the agents instead have a cigarette.
  - Movement
    - The event window is checked for the nearest RES location.
    - In the absence of available RES, each type will check for the nearest genetically favorable conditions in the event window, if such conditions exist.
    - A single-step move is made, biased towards that location
    - NPNAs will get down tonight.

Reproduction will involve selecting either parent's Altruistic and/or Parochial values at random, subject to some probability of mutation. Thus, a child could receive one or both of either parents values, potentially modified. Starting resources will likewise be a shared portion of both parents at a fixed amount. They immediately enter the world as teenagers, striking out on their own with no interest in cultivating a relationship with either parent and will probably get into drugs or run off to Hollywood or some similar nonsense.

====Questions Examined====

While the model I am attempting to create has roots in the work of Choi and Bowles, I am hoping to model a pre-paleolithic society; one more nomadic wherein the in-groups do not pool and share resources, nor do they engage in outright warfare with other groups. Rather, the interactions among agents are restricted to the individual territory of the agents themselves, reflecting a period before social coagulation took hold with early hominids, roughly 3-5 million years ago. ((Edward H. Judge & John W. Langdon. //Connections: A World History, Combined Volume, 2/E//. Pearson; 2 edition 2011)) This muddies the waters a little bit on what it exactly means to be an in-group, though Judge and Langdon point out that the process of forming groups was gradual and it would be on the order of millions of years before societies were more firmly established.

I suspect that altruism and parochialism were both still in the very early stages of development in this period and it would be interesting to see how each might have come about, and what the conditions were that made their appearance more probable. Will the simulation results reflect what Choi and Bowles propose, that Altruism and Parochialism reinforce each other? 

===So What? (Computer Science Edition)===

So what is the computational tie-in to all of this? Why do we, as computer scientists, care about how altruism and parochialism came about under pressure? And under traditional computational paradigms, these are legitimate questions. Processes don't attack other processes for the purposes of resource competition (they do for other reasons). They might be included in an group, and a group of processes belonging to a virus might very well be considered an out-group, but does the concept of sacrifice mean anything to a computational process? I would argue no, under the traditional computational paradigm of efficiency-first computing, the concept of altruism doesn't apply. 

Under robust-first computing however, under the resource-limited confines of the MFM, it might. If a program needs space to operate, it may very quickly need to start making sacrifices if that space is limited. If it is competing for space with other process groups, it may need to be aggressive. What constitutes the fitness of a program in a robust-first environment? Perhaps Parochial Altruism might be a successful behavior to engage in.