Announcements

For the Fall 2018 course see Blackboard!
[24 Jan. 2018] Exam grades are available here!
[10 Jan. 2018] Grades for the practial assignment are available here!
[7 Sept. 2017] The practial assignment is online!
[5 Sept. 2017] The first lecture will be on Tuesday September 12, appologies for any confusion.
Course description
Natural computing or natural computation is the field of research that works with computational techniques inspired by nature and natural systems. The aim of such research is to develop new computational tools for solving complex, usually conventionallyhard problems. This often leads to the synthesis of natural patterns, behaviors and organisms, and may result in the design of novel computing systems that use natural media with which to compute.
This course will give an introduction to various algorithms that are inspired by nature and show how they have proven to be very powerful in solving various kinds of problems.
Course regulations
There is a final written exam at the end of the course that will determine your final grade for 70%. The other 30% of your grade will be based on the practical assignment.
The final grade is computed as:
 Final grade = 0.7 * exam_grade + 0.3 * practical_assignment_grade
A successful completion of the course will be rewarded with 6ECTS.
Exam
The exam is closedbook and will be based on the lectureslides.
Practical assignment
In the practical assignment you are asked to solve a reallife optimization problem using algorithms from Natural Computing. It may be done individually or in pairs, and is to be implemented in MATLAB.
 The description of the PA: PA.pdf
 The MATLAB files for the PA: PA.zip
 Deadline: Friday December 8th, 2017, 12:00 (noon)
Running Matlab
Some instructions on how to start Matlab on the computers at the Snellius building, or what you can do if you do not want to use those computers are available here
Matlab tutorial
A Matlab tutorial is available below so you can practice if you are not yet familiar with Matlab.
 The Matlab tutorial MATLAB.pdf
 Solutions to tutorial exercises MATLAB_solutions.pdf
 Matlab Cheat Sheet in case you are familiar with Python or R CheatSheet.pdf
 The solution to the Autocorrelation function autocorrelation.m
 The solution to the Ackley function ackley.m
Course material & Schedule
The course slides and the current time schedule are as follows.

Lecture 1: [12 Sept. 2017  Building: Gorleaus, Room: Havingazaal]
 1a. Introduction
 1b. Practical Assignment Introduction
 1c. Introduction to Optimization Lecture 2: [19 Sept. 2017  Building: Huygens, Room: 106109]
 2a. Simulated Annealing
 2b. Particle Swarm Optimization Lecture 3: [26 Sept. 2017  Building: Gorleaus, Room: Havingazaal]
 3. Evolutionary Algorithms Lecture 4: [10 Oct. 2017  Building: Gorleaus, Room: Havingazaal]
 4a. Ant Colony Optimization
 4b. Ant Colony Optimization Lecture 5: [17 Oct. 2017  Building: Gorleaus, Room: Havingazaal]
 5a. Differential Evolution
 5b. Artificial Bee Colony Lecture 6: [24 Oct. 2017  Building: Huygens, Room: 106109]
 6. Nonlinear Dynamics Lecture 7: [31 Oct. 2017  Building: Huygens, Room: 106109]
 7a. Cellular Automata
 7b. Fractal Geometry Lecture 8: [7 Oct. 2017  Building: Huygens, Room: 211/214]
 8. Spiking Neural Networks Lecture 9: [14 Nov. 2017  Building: Gorleaus, Room: 02]
 9. LSystems Lecture 10: [21 Nov. 2017  Building: Sylvius, Room: 1531]
 10a. DNA Computing
 10b. Artificial Immune System Lecture 11: [28 Nov. 2017  Building: Sylvius, Room: 1531]
 11x. Preliminaries: Vector Space etc.
 11a. Quantum Computing: Motivation and Introduction
 11b. Quantum Computing: Linear Algebra and Deutsch's Problem
 11c. Deutsch's Problem Lecture 12: [5 Dec. 2017  Building: Sylvius, Room: 1531]
 12a. Genetic Programming
 12b. Firefly Synchronization
Sample exam
Find the exam of 2007 here.Answers to the Sample exam
Answer to the exam of 2007 hereSample questions
Find the sample questions of Firefly Synchronization and LSystems here.Exercises for Lsystems
Find the the exercises for Lsystems here.Recommended literature
Brabazon, Anthony, Michael O'Neill and Seàn McGarraghy  Natural Computing Algorithms
Springer (2015)
ISBNEbook: 9783662436318 \ ISBNHardcover 9783662436301
Leandro Nunes de Castro  Fundamentals of Natural Computing
Chapman & Hall/CRC; 1 edition (June 2, 2006)
ISBN10: 1584886439 \ ISBN13: 9781584886433
Marco Dorigo and Thomas Stützle  Ant Colony Optimization
MIT Press (6 Jul 2004)
ISBN10: 0262042193 \ ISBN13: 9780262042192