Biology inspired computing

Course title

Code

F18L3S078

Study programme

—

Organizer of the study programme (unit, institute, department)

Faculty of Computer Science and Engineering

Degree level (first, second, third cycle)

First cycle

Academic year / semester

8 / Summer

Number of ECTS credits

Teacher

—

Prerequisites for enrolling in the course

Алгоритми и податочни структури и Вештачка интелигенција

10.

Course objectives (competences)

The goal of this course is to introduce students to algorithms inspired by naturally appearing phenomena and their application in solving problems in optimization, design and learning. The focus will be on algorithms abstraction from the observed phenomena, analysis and comparison of their results. Within the course special attention will be given to specific applications to the aforementioned algorithms. Upon completion students should acquire the following:
- Knowledge of naturally occurring phenomena that are the inspiration for the learned algorithms
- Understanding of the strengths and weaknesses of learned algorithms
- Ability to identify the appropriateness of learned algorithms and their application to problems of optimization, design and learning

11.

Course content

Introduction to biologically inspired computation; Search and optimization;
Local search techniques;
Genetic algorithms;
Genetic programming;
Swarm intelligence; Ant colony optimization;
Particle swarm optimization; Artificial bee colony;
Artificial immune systems;
Neural networks;
Self-organizing neural networks;
Constraint satisfaction;
Other biologically inspired heuristics;

12.

Learning methods

Lectures using presentations, interactive lectures, exercises (using equipment and software packages), teamwork, case studies, guest lecturers, independent preparation and defense of a project assignment and a seminar paper.

13.

Total available time

6 ECTS x 30 hours = 180 hours

14.

Distribution of the available time

30 + 45 + 15 + 15 + 75 = 180 hours

15.

Forms of teaching activities

15.1.	Lectures – theoretical teaching	30 hours
15.2.	Exercises (laboratory, auditory), seminars, team work	45 hours

16.

Other forms of activities

16.1.	Project assignments	15 hours
16.2.	Individual assignments	15 hours
16.3.	Home study	75 hours

17.

Grading

17.1.	Tests	10 points
17.2.	Seminar paper / project (presentation: written and oral)	15 points
17.3.	Activity and participation	10 points
17.4.	Final exam	70 points

18.

Grading criteria (points / grade)

up to 50 points	5 (five) (F)
from 51 to 60 points	6 (six) (E)
from 61 to 70 points	7 (seven) (D)
from 71 to 80 points	8 (eight) (C)
from 81 to 90 points	9 (nine) (B)
from 91 to 100 points	10 (ten) (A)

19.

Requirements for signature and taking the final exam

Activities 15.2 and 16.1 have been completed.

20.

Language of instruction

Macedonian and English

21.

Method of monitoring teaching quality

internal evaluation and survey mechanism

22.

Literature

22.1.	Required literature No. Author Title Publisher Year
22.2.	Additional literature No. Author Title Publisher Year