Implementation of many popular AI algorithms to play the game of Pacman such as Minimax, Expectimax and Greedy.
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Updated
Apr 12, 2020 - Python
Implementation of many popular AI algorithms to play the game of Pacman such as Minimax, Expectimax and Greedy.
Artificial Intelligence search algorithm base on Pacman
Reinforcement Learning Course Project - IIT Bombay Fall 2018
Implementation of BFS, DFS, A*, HillClimber, Genetic, MCTS Agents
Deep Reinforcement Learning Pacman in Pytorch
The course contest involves a multi-player capture-the-flag variant of Pacman, where agents control both Pacman and ghosts in coordinated team-based strategies
A Pacman game implementation with an AI player using the Minimax algorithm. This project showcases the classic Pacman game environment, where the player (Pacman) navigates a maze to collect points while avoiding ghosts. The AI-controlled ghosts aim to catch Pacman.
My solutions to projects 1, 2 & 3 of Berkeley's AI course
Implementation of projects 0,1,2,3 of Berkeley's AI course
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
Partially observable PacMan game in OpenAI Gym format
💾 A python3 version of Berkeley's Pacman AI course
Exploring Learning Algorithms with Pac-Man
Implementations of artificial intelligence agents that plays Pac-Man
Pacman agent will search paths from maze to arrive at a certain destination and collect food efficiently
A repository for the Solutions for the PacMan assignment from Berkley
Solutions of Pacman projects of Berkeley AI course
Agents for Berkeley AI Capture the Flag tournament.
Assignments of the HKU Course on Artificial Intelligence. Contains implementations of search and pruning algorithms, value iteration, q-learning and joint particle filters
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