
	The completed program performed in accordance with the expected results. After multiple generations, anims did grow to be more adapted to their environments in terms of utilizing movement efficiently, hunting other anims, and selecting a safe environment. Growth was measured in terms of increased overall energy after runs, as well as in terms of the average death rate. It was found that all species developed predatory habits at roughly the same rate, which prevented any one species from becoming a dominant force. An unexpected result was the increased number of generations needed to increase the net energy gain for a species significantly; sometimes, over 1000 generations were required. However, the program performed as predicted, with no noticeable glitches or malfunctions in the coding. 
	The purpose of this research project was to determine the viability of genetic algorithms in simulating the foraging theory of animals in dynamic biological systems. It was predicted that the use of genetic algorithms would significantly impact the growth rate of the skills of the simulated creatures. Overall, the creatures displayed a high level of learning and evolution throughout the program’s runs.
	The screenshot given exhibits the growth of the anims (measured in energy gain) after a 250-generation run.
	These results are similar to the results achieved by Mat Buckland’s genetic algorithm for solving simple math problems. Since this project utilized similar techniques to that program, it is easy to draw parallels between the two and concur that they both reached a common goal using the same basic functionality. Moving away from the strictly programming aspect, one can compare the biological situations in the projects conducted by Clark, Houston, Mangel, and McNamara. In “Towards a Unified Foraging Theory”, Clark and Mangel define a series of variables that can be used in simulating the foraging techniques of a unique organism. The program utilized a similar set of variables that dealt with things such as energy, food, predators, and movement. In the section of the paper dealing with patch selection (a parallel to the environment selection of the program), it is surmised that the forager will adopt slightly more hazardous strategies as its energy level drops. However, this effect, as well as similar predictions made by the UFT, are not present within the program. In “Dynamic models in behavioural and evolutionary ecology”, Clark et al. describe multiple scenarios that can be applied to the theory of dynamic models. Several of them, such as the dawn chorus and the clutch size in insects, have no relation to the program. Others, such as the small birds in winter  scenario, are directly related. The birds are given a choice; forage or find a mate. There is an arbitrary energy reward for succeeding at either of these tasks, but the key is selecting the combination with the highest payoff. Like the hunt vs. scavenge selection in the program, the anims eventually opted for predation in order to get more energy overall. 