This is the fourth part of the Pacman AI project. In this part of the project, the Pac-Man agents are designed to use sensors to locate and eat invisible ghosts. Task difficulty changes from tracking single, stationary ghosts to hunting packs of multiple moving ghosts with ruthless efficiency.
This is the third part of the Pacman AI project. In this part of the project, I implemented value iteration agent, a Q-learning reinforcement learning agent, and an approximate Q agent.
This is the second part of the Pacman AI project. In this part of the project, I implemented the Reflex agent, Minimax agent, Alpha-Beta agent and Expectimax agent.
Introduction This is the first part of the Pacman AI project. In this part of the project, I implemented several search algorithm, such as DFS, BFS, A*, UCS, Sub-optimal Search etc. In this post, I will also discuss how these algorithms can turn into each other under certain conditions. Implementation of Algorithms The implementation of... Continue Reading →
This project was done when I was pursuing the certificate in Deep Learning Specialization taught by Andrew Ng on Coursera. It was a programming assignment for the first course in the specialization. The project goal is to train a neural network that can tell if an image is a photo of a cat. It is a... Continue Reading →