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Monte-Carlo Tree Search (MCTS) and Heuristic Search for Pacman Agent Design

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This project is based on the "Contest: Pacman Capture the Flag" project in the UC Berkeley CS188 Intro to AI Course. Three techniques of Pacman AI are implemented: Heuristic Search, Monte-Carlo Tree Search (MCTS), and PDDL.

Contributors:

Teeraroj Chanchokpong: Heuristic Search Agent (agent 1)

Davis Hong: Monte-Carlo Tree Search Agent (agent 2)

JamesAndrewRogers: PDDL agent

http:https://ai.berkeley.edu/projects/release/contest/v1/002/capture_the_flag.png

Environment: Python 2.7

Run:

# -r: red team
# -b: blue team
# detailed commands on CS188 Intro to AI
python2 capture.py -r baselineTeam.py -b disabledPacman.py -l RANDOM2

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Monte-Carlo Tree Search (MCTS) and Heuristic Search for Pacman Agent Design

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