Checking date: 24/04/2024

Course: 2024/2025

Artificial Intelligence of Biological Inspiration
Master in Computer Science and Technology (Plan: 462 - Estudio: 71)

Coordinating teacher: ISASI VIÑUELA, PEDRO

Department assigned to the subject: Computer Science and Engineering Department

Type: Compulsory
ECTS Credits: 3.0 ECTS


Requirements (Subjects that are assumed to be known)
Nature inspired techniques have recently become very important within the field of Artificial Intelligence. The course aims to introduce students to these techniques, in its most advanced aspects. The key objectives are to help students understand the theoretical foundations of these techniques, how they can be used to solve problems, and in which areas are most useful and effective. The biologically-inspired techniques are based, mainly, on two separate paradigms, Genetic Algorithms and Neural Networks. Both paradigms are covered in the course, as well as the relationship between them and their combined use to expand the effectiveness of problem solving separately.
Skills and learning outcomes
Description of contents: programme
1. Introduction to bio-inspired computing techniques     1.1. Biological inspiration in engineering     1.2. General concepts of evolutionary algorithms 2. Genetic systems 2.1. Genetic Algorithms 2.2. Evolutionary Strategies 2.3. Genetic Programming 2.4. Genetic Expressions 3. Swarm systems     3.2. Particle Swarm Optimization     3.3. Ant Colony Optimization     3.4. Swarm Robotics 4. Emerging systems 4.1. Complex adaptive systems 4.2. Self-organized systems     4.3. Cellular Automata     4.4. Evolution of strategies of cooperation / competition 4.5. Coevolution 4. Alternative bio-inspired systems     5.1. Glowworm Optimization 5.2. Diferential Evolution 5.3. Artificial Inmune Systems 5.4. Other bio-inspired methods 5.5. Applications in real problems 6. Neural systems 6.1. Supervised Neural Networks 6.2. Unsupervised Neural Networks   
Learning activities and methodology
1. Theoretical classes. magisterial teaching of the theoretical concepts of the course contents and their practical and applied aspect classes will be held. 2. Practical Case. Students must choose a case of problem resolution proposed by teachers and perform one of: 2.1 A critical analysis. 2.2 An implementation of the problem and experimentation environment in which they must be able to develop an analysis and conclusions on the case study. 3. Oral presentation. Students must perform in the classroom in front of their peers, an oral presentation and defense of case study developed. 4. tutorials will be conducted, both onsite and remotely.
Assessment System
  • % end-of-term-examination 0
  • % of continuous assessment (assigments, laboratory, practicals...) 100

Calendar of Continuous assessment

Basic Bibliography
  • D. Floreano, C. Mattiussi. Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies. The MIT Press. 2008
Additional Bibliography
  • Gary William Flake. The computational beauty of nature. MIT Press. 1998

The course syllabus may change due academic events or other reasons.