vitorverasm/ai-nqueens

This is a n-queen problem solver using local search algorithms.

24
/ 100
Experimental

Implements three distinct local search strategies—Hill Climbing, Hill Climbing with random restart, and Simulated Annealing—each evaluated against a heuristic measuring queen-pair conflicts. The CLI tool accepts configurable board size and iteration counts, comparing success rates and runtimes across all algorithms in a single run. Board solutions are visualized as ASCII grids with detailed performance metrics for empirical algorithm comparison.

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Language

Python

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Last pushed

Feb 26, 2018

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