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The project was implemented in the context of the course "Artificial Intelligence (AI)" at the Technical University of Crete

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Weighted A* & IDA* algorithm implementation for pathfinding in grid maps

This repository contains an implementation of the Weighted A* and the Iterative deepening A* (IDA*) algorithms for pathfinding in grid maps, with two heuristic functions based on Euclidean distance and Manhattan distance.

The implementation is written in Python and includes various scenarios with different start and goal locations, as well as obstacles. The project also allows for experimentation with different values of the weight parameter to optimize the algorithm's performance in each scenario.

The results are displayed on the screen and in an output file for each algorithm and scenario, including the number of expanded nodes, the path proposed by the algorithm, and the value of the selected heuristic function.

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The project was implemented in the context of the course "Artificial Intelligence (AI)" at the Technical University of Crete

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