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.
Deep Reinforcement Learning Pacman in Pytorch
Reinforcement Learning Course Project - IIT Bombay Fall 2018
Pacman agent will search paths from maze to arrive at a certain destination and collect food efficiently
Pacman using c++ and Computer Graphics.
Implementations of artificial intelligence agents that plays Pac-Man
Array of AI Search algorithms is employed to playing Pac-Man ⍩⃝.
In this project, agents are designed for the classic version of Pacman, including ghosts. Mini-max, Alpha-Beta pruning, Expectimax techniques were used to implement multi-agent pacman adversarial search.
Partially observable PacMan game in OpenAI Gym format
Implementation of reinforcement learning
In this project, the Pac-Man agent finds paths through its maze world, both to reach a particular location and to collect food efficiently. Search algorithms such as Depth First Search, Bread First Search, Uniform Cost Search and A-star search are applied to Pac-Man scenarios.
MCTS Pacman agent applied to the Pacman VS Ghosts conpetition framework
💾 A python3 version of Berkeley's Pacman AI course
(Berkeley AI) Multiagent problems using PACMAN
The Fundamentals of Artificial Intelligence Course Projects.
Pacman Agent: an artificial intelligent agent that plays Pacman.
A Pacman game agent that uses a modified version of the Monte-Carlo Tree Search to play the game
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