A Keras Implementation of Attention_based Siamese Manhattan LSTM

Eight Puzzle solver using BFS, DFS & A* search algorithms

8-puzzle game that features a walkthrough of the optimal solution and allows users to customize the tiles using photos from their Gallery

A C++ implementation of N Puzzle problem using A Star Search with heuristics of Manhattan Distance, Hamming Distance & Linear Conflicts

Linkage Methods for Hierarchical Clustering

Sliding Puzzle solver and utilities

C++ implementation of IDA* algorithm for solving the 15 and 25 puzzle

Complete Java Approach

A sliding puzzle game and solver using ncurses.

C codes for the Arificial Intelligence Course and algorithms.

Classic n-puzzle problem solver using A* search

A Java console application that implements the factionality of the knn algorithm to find the similarity between a new user with only a few non zero ratings of some locations, find the k nearest neighbors through similarity score and then predict the ratings of the new user for the non rated locations.

🕹 Algoritmo que resolve o jogo dos oito por busca em profundidade(sem estados visitados), busca em largura(com estados visitados), busca gulosa(com estados visitados) e busca a*(com estados visitados). Podendo mostrar passo a passo das escolhas dos nós e mostrando a árvore resultante(até um certo limite ou completa) do método de busca selecionado.

Python 3 library for Multi-Criteria Decision Analysis based on distance metrics, providing twenty different distance metrics.

Machine learning functions written in goLang:

KNN movie recommendation system using python 🎥✨

Solves puzzles of various sizes

The N-puzzle is a sliding puzzle that consists of a frame of numbered square tiles in random order with one tile missing. The puzzle can be of any size, with the most common sizes being 3x3 and 4x4. The objective of the puzzle is to rearrange the tiles to form a specific pattern.

Functions for generating Voronoi diagrams with alternate metrics.

An efficient Nearest Neighbor Classifier for the MINST dataset. It uses a VP Tree data structure for preprocessing, thus improving query time complexity