You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
A project that applies several Artificial Intelligence techniques such as informed state space search, reinforcement learning and probabilistic inference. Algorithms such as Depth First Search, Breadth First Search, Uniform Cost Search, A-star Search enabled the pacman to win in different game versions
Explore foundational AI concepts through the Pac-Man projects, designed for UC Berkeley's CS 188 course. Implement search algorithms, multi-agent strategies, and reinforcement learning techniques in Python, emphasizing real-world applications. Engage in the Eutopia Pac-Man contest for a multiplayer capture-the-flag challenge
🕹️👻👾👻 In this thrilling AI adventure, we embark on a multi-stage quest to transform Pacman into an intelligent game-playing agent. Across three engaging projects, we explore various facets of artificial intelligence, from basic search algorithms to adversarial competition and reinforcement learning.
A variation of Pacman arcade game designed to train Pacman agents that use sensors to locate and eat invisible ghosts with phenomenal efficiency. Used Joint Particle Filter algorithm in AI to get 30% optimized results.