Game Theory is the study of strategic decision making. Mainly used for economics, political science, and psychology, it allows us to construct mathematical model strategies for decision-making in conflictual and cooperative situations. Co-evolutionary game theory is the application of game theory to evolving populations in biology and focuses on intra and inter-specific competition. Examples include predator-prey competition. The problem present is to determine different hunting tactics for the predators and different evading tactics for the prey to determine what is the best strategy for each species.

The aim of this project is to develop a computer simulation that models a competitive non-mutualistic inter-species co-evolutionary system with different predator vs prey scenarios to select the best strategy for the prey and the predator through evolutionary game theory concepts. Through this, I hope to obtain a better understanding of coding using python and understand Game Theory and how to apply it to other topics.

To do this, I will use python to simulate different predator vs prey models. Using a payoff matrix, I will be able to visualize the different payoffs present with each strategy and then determine which strategy the player should choose.

Results that I can expect to come across are the Nash Equilibrium, symmetric payoffs, and saddle point payoffs. These results will be obtained using programming software such as python.

This research will be able to provide a mathematical model to visually represent predator vs prey models and the strategies used by the prey and predators using payoff matrices.