This Artificial Intelligence project provided an area to build and implement common AI functionalities. Through the weeks in GSP315, state systems, behavior trees, fuzzy logic, random number generation, and learning algorithms were explored. As the final deliverable for the course, this demo was developed where two ships, one player controlled and the other an autonomous unit, move about the play field and interact. The AI unit will default to wandering but will attempt to avoid the player ship. With the help of fuzzy logic and an N-Gram system, the game logs the player movements every second and forwards that information to the AI ship. As the game plays, the AI ship begins to learn how the player will move and will avoid where it think the player will be rather than where it is. On purpose, the AI ship starts slow and able to be caught but will steadily grow to a point where it cannot be caught.

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The skills presented in this project were further developed in the Advanced AI class, GSP480, as my specialization.  Movement algorithms grew to include pathfinding algorithms like Dijkstra, Heuristics, A* and more.  Statistical processing and problem solving algorithms expanded with Monte Carlo methods, Solution Trees, and Neural Networks.