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AI Course Project

This Repo contains comprehensive AI course projects that covers various aspects of artificial intelligence, including search algorithms, game development, Markov decision processes, and deep learning.

  • Artificial Intelligence Course - Fall 2024

Phase 1: Solving Rubik's Cube with Search Algorithms

In this phase, several search algorithms were used to solve the Rubik's Cube problem, including Random Search, Iterative Deepening Depth-First Search (IDS-DFS), A* Search, and Bidirectional Breadth-First Search (BiBFS).

Phase 2: Rollit with Pygame

A game of Rollit was developed using Pygame. The game is a multiplayer game where each player takes turns to place pieces on a grid. A minimax algorithm with alpha-beta pruning was used to determine the best move for each player.

Phase 3: MDP and Reinforcement Learning

In this phase, a Markov Decision Process (MDP) was used to optimize a policy for the Frozen Lake environment. Q-learning was used to learn the optimal policy and promising results were obtained.

Phase 4: Deep Q-Networks for Snake Game

In this phase, a neural network was used to play the game of Snake using Q-learning. A deep Q-network was used to approximate the Q-function and promising results were obtained.

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Artificial Intelligence Course - Fall 2024

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