https://github.com/andi611/pacman-with-ai-python
Implementations of artificial intelligence agents that plays Pac-Man
https://github.com/andi611/pacman-with-ai-python
a-star-search alpha-beta-pruning artificial-intelligence breadth-first-search depth-first-search expectiminimax minimax-search pacman pacman-agent uniform-cost-search
Last synced: 9 days ago
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Implementations of artificial intelligence agents that plays Pac-Man
- Host: GitHub
- URL: https://github.com/andi611/pacman-with-ai-python
- Owner: andi611
- License: mit
- Created: 2019-04-09T16:36:07.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2019-04-10T13:03:56.000Z (over 6 years ago)
- Last Synced: 2025-07-26T11:03:02.784Z (3 months ago)
- Topics: a-star-search, alpha-beta-pruning, artificial-intelligence, breadth-first-search, depth-first-search, expectiminimax, minimax-search, pacman, pacman-agent, uniform-cost-search
- Language: Python
- Size: 556 KB
- Stars: 8
- Watchers: 0
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Artificial Intelligence in Pacman
Class material offered in the course "Artificial Intelligence (2019 Spring) of NTU"
## Search Agents
### Implementation:
* [search.py](task1_Search/search.py)
* Please refer to this [README](task1_Search/README.pdf) for more information.
### Algorithms:
* Depth First Search (DFS)
* Breadth First Search (BFS)
* Uniform Cost Search (UCS)
* A Star Search (ASS)
## Multi-Agents
### Implementation:
* [multiAgents.py](task2_Multiagent/multiAgents.py)
* Please refer to this [README](task2_Multiagent/README.pdf) for more information.
### Algorithms:
* Rule Base Reflex
* Minimax Search
* Alpha-Beta Pruning
* Expectiminimax Search