Artifical-Intelligence

This class was one of my dearest and also enjoyable. During this course we developed some AI agents and get a glimpse about neuronal networks. Such agent behaviors include searching, game playing, decision making, and learning.

Projects

• 1 Fundamentals of AI

  • The Fundamentals of AI Lab Project was a review of basic data structures and an introduction to behavioral modelling using the Behavior Tree concept.

• 2 Path Planner

  • This lab has multiple files zipped. each of them implements a search algorithm: A*, BFS, Greedy, Uniform cost search. I still remember this lab because it set the foundations of my professional career. Also the visualization and time calculation of each algorithm made it fun to research.

• 3 Flocking
  • Steering behaviors are algorithms that provide autonomous objects the ability to navigate their surroundings in a life-like or improvised manner. This lab covered the three main algorithms used in flocking, a type of steering behavior. These three algorithms are alignment, cohesion and separation. I suggest playing with the application UI to understand how does each algorithm interfere with the agents movement. A good read is this

• 4 Reversi
  • is a very popular strategy board game where the goal is flipping the opponent's pieces. During this project we implemented MiniMax algorithm to create the "perfect" agent. The Minimax Algorithm is a simple, predictive game playing technique where the agent assumes that the opponent makes “perfect” moves. The Minimax Algorithm attempts to maximize the probability of a win but assumes that the opponent will always make the best move and in so doing minimize the probability. This minimizing / maximizing behavior is where Minimax gets its name. Minimax is a type of Depth-First search where its ply represents a move either by the agent or the opponent.

• 5 Ms Pacman
  • This is a version of Ms. Pac-Man that closely represents the original game. The representation has a few minor changes to make writing the AI for both Ms. Pac-Man and the Ghosts fair. For additional information you can reference the official website from which this AI project originates at www.pacmanvs-ghosts.net. The fun fact about this project is that we made a small competition among all students and the agent with the highest score got some swag (and some extra credit). The program displays one run of the game, however, it gives the total score on the Eclipse output window which is gathered after 100 games.

Contributing

Please read CONTRIBUTING.md for details on the code of conduct, and the process for submitting pull requests to me.

Authors

• Ed Younskevicius - Course Director
• Jagoba "Jake" Marcos - Cabrra

License

This project is licensed under the MIT license - see the LICENSE file for details

Acknowledgments

• Full Sail University - Game Development Department
• Ed Younskevicius