Coursework done as part of the Artificial Intelligence Course @ Sofia University, Faculty of Mathematics and Informatics 2020/2021
The following solutions were implemented using different Artificial Intelligence algorithms.
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Decision Tree Classification for Breast Cancer - implements the ID3 algorithm for decision tree classification, using cross-validation to evaluate its accuracy on a breast cancer dataset. Solves the problem of classifying recurrence and non-recurrence events based on patient attributes
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Tic Tac Toe Game - implements a console-based Tic Tac Toe game where a player competes against the computer. The computer uses the Minimax algorithm with alpha-beta pruning to determine the optimal moves. It ensures competitive gameplay and provides feedback on the game's outcome.
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Travelling Salesman Problem - implements a genetic algorithm to solve the Traveling Salesman Problem (TSP). Creates a population of potential solutions (routes) over generations by using selection, crossover, and mutation to minimize the total travel distance.
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Naive Bayes Classifier - implements a Naive Bayes classifier to predict the political party affiliation (democrat or republican) based on voting data. It uses Gaussian probability and 10-fold cross-validation to evaluate its classification accuracy.
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N Queens Problem - implements a solution for the N-Queens problem using a stochastic local search approach with conflict minimization. The goal is to place N queens on an N×N chessboard so that no two queens threaten each other.
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N Pruzzle Problem - implements a solution for the N-Puzzle problem using the Iterative Deepening A* (IDA*) search algorithm. It focuses on finding the shortest path from a given start board to the goal board, verifying solvability, and using Manhattan distance as the heuristic for efficient pathfinding.
More information can be found in each subfolder's README for the corresponding problem.