Term 1 Project 2 Implement a Planning Search by Luke Schoen for Udacity Artificial Intelligence Nanodegree (AIND)

Sudoku solver that models the puzzle as Constraint Satisfaction Problem

Travelling Salesperson Problem solved using various genetic algorithms

Randomly displays software testing -based heuristics

Construction heuristics for the multidimensional knapsack problem (MKP)

Appunti del corso di Intelligenza artificiale (a.a. 2017/2018) - università degli studi di Padova

Facility location problem solved in Go

Code, Präsentationen und Dokumente für das Maschinenbelegungsseminar bei Prof. Buscher zu meinem Thema Cloud Manufacturing.

A rudimentary chess game application with a command-line interface. Written in C.

Agents for various games

Solver for the Ore Mixing Problem (OMP) and the Unrelated Parallel Machine Schedule Problem (UPMSP).

Implementation of the paper "Optimisation of Deep Neural Networks using a Genetic Algorithm: A Comparative Study" by Tiago Gonçalves, Leonardo Capozzi, Ana Rebelo and Jaime S. Cardoso.

Heuristics Lesson Lab Codes

A lightweight library for particle swarm optimization. The library is designed to be easily extended with new metaheuristic optimization algorithms and optimization problem types in the future.

A sliding puzzle solver, using the A* search algorithm with several heuristics

Travelling Salesman Solution w/ Nearest Neighbor Heuristic

Solver for the Google Hash Code 2019 Final

Berkeley Pacman Projects (1 and 2), Depth First Search, Breadth First Search, Uniform Cost Search ,A* Search , Heuristic Functions ,Suboptimal Search, Minimax Algorithm, Alpha-Beta Pruning, Expectimax, Constraint Santisfaction Problems, RLFA CSP problem, Propositional Logic, First-order Logic

Codes for the assignments of the Artificial Intelligence Course at Amirkabir University of Technology

A taxi domain modeled in PDDL. The objects in the chosen domain are taxis, people, and sidewalks. Taxis can park along a sidewalk or double-park and can move from one sidewalk to another