The Paralta simulation is made up of three elements We introduce Sytizen; Why stock parameters change on dreg and res *Dynamic Regulators (DREGs): Produce RES and can destroy nearby elements with small probability. *Resources (RES): A resource of the world. RES diffuse around the world until consumed. *Sytizens: A denizen of the simulation world. DREGs are set with the following parameters: * Spawn RES with a set probability. * Delete nearby Elements with probability 0.01 * Spawn other DREGs with probability 0.002 * Delete other DREGs with probability 0.02 RES are consumed by Sytizens with the following parameter: * 10 points of energy per consumed RES Each Sytizen is represented by the following parameters: * Team - an integer value representing the in-group of the Sytizen. * Energy - an integer value initialized to 20. * res grant 10 energy * Genotype - the genetic makeup of the Sytizen that determines its overall behavior in the world. This is represented by two 4-bit values values: * Parochialism - a value 0 =< p =< 7 indicates a non-parochial individual, while a value 7 > p >= 15 implies a parochial citizen. * Altruism - a value 0 =< a =< 7 indicates a non-altruistic individual, while a value 7 > a >= 15 implies an altruistic citizen. The Genotype parameter combinations (produce?) to four discrete phenotype categories: Parochial Altruist (PA): The behavior of a parochial altruist is to attempt to kill one out-group member encountered within a Manhattan distance of 2 with 0.5 probability of success. If this attempt fails, the PA dies with probability 0.5. Movement is additionally biased towards out-group members. Parochial Non-Altruists (PNA): PNAs will attempt to injure one out-group member within a Manhattan distance of 2 at a reduced risk to themselves. With 0.5 probability, the victim will suffer a loss of 10 energy. If the attack fails, the attacker will suffer the same energy loss with 0.5 probability. Non-Parochial Altruists (NPA): Upon encountering an in-group member with low energy within a Manhattan distance of 2, NPAs will share an amount of their resources equal to half the difference in energy, less a sharing threshold of 20. Movement is additionally biased towards in-group members. Non-Parochial Non-Altruists (NPNA): No specialized behavior. At the beginning of an event, a Sytizen will first pay a metabolism cost of 1 energy. If this depletes the energy to 0, the Sytizen is removed and the event ended. The neighborhood of the Sytizen is then scanned, and the location and type of any Element or empty space is recorded within a Manhattan distance of 4. The Sytizen will then consume one neighboring RES within 2 Manhattan distance from them. A consumed RES bestows 10 energy on the Sytizen. Then, any genetic-specific behavior is performed. If the Sytizen is still alive and their total energy is greater than 40, they will attempt to procreate. Any in-group members within a Manhattan distance of 2 are sorted by energy. If the highest energy amount is greater than 40 RES, that Sytizen is selected to breed. If an empty location is available, an offspring will appear with a starting energy of 20, and the energy of each parent reduced by 20. The offspring will inherit one of the parent's Altruism values and Parochial values with 0.5 probability each. Thus, a PA and an NPNA could produce any of the 4 categories of phenotype. Once the genes are established, the parochial and altruism values are subject to mutation with probability 0.004. If a mutation occurs, the new value is chosen uniformly at random from 0 to 15. Finally, the Sytizen engages in movement. All Sytizens, in addition to their genetic movement bias (if any), are also movement-biased towards any RES visible to them in a given event. They take a single step, and the event is concluded. We vary the probability that DREGs produce RES in the environment to simulate various states of resource scarcity. The spawn rates are 0.02, 0.01, 0.0067, and 0.005 for the respective runs. We conduct 5 simulation runs for each scarcity category. Simulations are run for 10 kAEPS or until only 1 group remains. We then analyze the phenotype categories within the population over the life of the simulation.