This repository contains a collection of implementations of various computational intelligence algorithms.
"Computational intelligence" as a field is at the intersection of artificial intelligence, machine learning and computer science techniques. A computational intelligence algorithm is an algorithm that learns to solve problems from observations (data) in a biologically inspired way.
To get familiar with the key concepts of this field, three different computational intelligence algorithms were implemented:
- Ant Colony Optimization: to solve the travelling salesman problem
- Artificial Neural Network: to classify products such as fruits or candy by detecting a number of separate features such as roundness or color
- Q Learning: to replicate an agent finding a way through a maze based on reinforcement learning
Taken together, these three algorithms should simulate a robot who is capable of autonomously picking up different items in a supermarket.
| Purpose | Name |
|---|---|
| Programming language | Java, Jupyter Notebook |
| Version control system | Git |
These algorithms were implemented together with:
These computational intelligence algorithms are published under the MIT licence, which can be found in the LICENSE file. For this repository, the terms laid out there shall not apply to any individual that is currently enrolled at a higher education institution as a student. Those individuals shall not interact with any other part of this repository besides this README in any way by, for example cloning it or looking at its source code or have someone else interact with this repository in any way.
The image in the logo was taken from the website of the Computational Intelligence Society.
