https://github.com/cheind/py-classic-ai
Various classic artificial intelligence algorithms applied to common problems.
Science Score: 26.0%
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Low similarity (5.8%) to scientific vocabulary
Keywords
Repository
Various classic artificial intelligence algorithms applied to common problems.
Basic Info
- Host: GitHub
- Owner: cheind
- License: bsd-3-clause
- Language: Python
- Default Branch: master
- Size: 13.7 KB
Statistics
- Stars: 3
- Watchers: 2
- Forks: 1
- Open Issues: 0
- Releases: 0
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Metadata Files
README.md
py-classic-ai
Various classic artificial intelligence algorithms applied to common problems.
connectfour.py
Connect Four is a two player game where one player attempts to connect 4 discs (horizontally, vertically or diagonally) while preventing the other player from doing so. The code allows you to play the game against a artificial agent utilizing a depth limited adversarial MiniMax search to determine its next move. In particular, the implementation is based on Negamax and uses Alpha-Beta pruning to quickly discard search regions.
sudoku.py
Sudoku is logical number puzzle game. The objective is to fill a 9x9 grid with digits such that each digit from 1 to 9 occurs exactly once along each row, each column and each 3x3 sub-grid. According to this article the fewest number of cells filled for a unique solution is 17. The solver implemented is based on greedy search utilizing a depth-first search traversal and a heuristic that sorts potential moves based on the number of unconstrained neighbor cells for a given cell. The more numbers along the cell's row/column/sub-grid are known, the better the heuristic. The heuristic works well in practice and leads to almost always a solution when reaching the first leaf. Occasionally, when only few cells are filled from the beginning, multiple digit choices are available for a single cell and the algorithm might fail to choose the correct one. However it will backtrack to the correct solution if there is one.
Owner
- Name: Christoph Heindl
- Login: cheind
- Kind: user
- Location: Austrian area
- Website: https://cheind.github.io/
- Repositories: 88
- Profile: https://github.com/cheind
I am a computer scientist working at the interface of perception, robotics and deep learning.
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