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
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Updated
Jan 24, 2021 - Python
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
Implementation of many popular AI algorithms to play the game of Pacman such as Minimax, Expectimax and Greedy.
My solutions to projects 1, 2 & 3 of Berkeley's AI course
Reinforcement Learning Course Project - IIT Bombay Fall 2018
Artificial Intelligence search algorithm base on Pacman
Implementation of BFS, DFS, A*, HillClimber, Genetic, MCTS Agents
Deep Reinforcement Learning Pacman in Pytorch
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.
Pacman using c++ and Computer Graphics.
Implementations of artificial intelligence agents that plays Pac-Man
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
MCTS Pacman agent applied to the Pacman VS Ghosts conpetition framework
A software framework to learn algorithms like AI planning, behaviour trees, and reinforcement learning.
Partially observable PacMan game in OpenAI Gym format
💾 A python3 version of Berkeley's Pacman AI course
Pacman agent will search paths from maze to arrive at a certain destination and collect food efficiently
Exploring Learning Algorithms with Pac-Man
A repository for the Solutions for the PacMan assignment from Berkley
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