defector | Captive portal authenticator Subgraph OS | TLS library

I am trying to replicate the results of a paper (if you are interested, its Nowak & May, 1992: Evolutionary Games and Spatial Chaos) that create a set of fractals by running a prisoners dilemma on an n x n grid (for example, https://www.researchgate.net/figure/Spatial-version-of-the-Prisoners-Dilemma-for-symmetrical-initial-conditions-Nowak_fig3_277476479), but my results are not what they should be. The idea is that the grid is populated entirely by Cooperators, except for a single Defector object that is placed in the center of the grid. Different interactions yield different payoffs: mutual defectors yield a payoff of 0, mutual cooperators a payoff of 1 each, and a defector against a cooperator yields a payoff of b for the defector and 0 for the cooperator, where b > 1. All objects in the grid play against each other and receive a score according to the above payoff structure. After each generation, each object on a node is replaced by the neighbor with the highest score. Since the defector strategy is the superior strategy, it should invade the Cooperator population and produce said fractal images, as a cellular automata would.

The main way I have tried doing this (also the main area I have had trouble with) is through the replace_pop function shown below. After each round, the program loops through the grid and replaces any object on a node with a neighbour object that has a higher score. I thought that this would have been sufficient but as one can see after even a few generations, there is some form of replication but just not in the way it should happen, making it difficult to pinpoint what exactly is going wrong. At N = 1 (N is the number of generations) the result seems correct, as the neighbouring (neighbours are left, right, above and below) Cooperators become Defectors, but as N grows larger the image just goes astray.

I also reinitialized each objects score to 0 after each generation to ensure that proper replication can take place. When this is not done however, the population evolves in the same fashion as the N = 1 case above but for all subsequent generations, which is peculiar because there should be defectors that have higher scores than surrounding Cooperators. I am not sure where I am going wrong? My code is below (sorry for including all of it but I do not know where exactly is the problem). I am pretty new to Python and Stack so any help would be appreciated.