Checking date: 03/05/2019

Course: 2021/2022

Unconventional Computation
Study: Master in Computer Science and Technology (71)


Department assigned to the subject: Department of Computer Science and Engineering

Type: Electives
ECTS Credits: 3.0 ECTS


Requirements (Subjects that are assumed to be known)
The course introduces advanced nonconventional computing techniques. The students will learn the theoretical fundations of these techniques, how they can be applied to solve problems, and in which cases they are more useful or efficient than other techniques. Nonconventional techniques are based in paradigms like DNA computing, quantum computing and artificial immune systems. These paradigms will be studied, their relationship and their joint application.
Description of contents: programme
- Introduction - DNA Computing - Quantum Computing - Biological Approach to Computing: -- Algorithms based on Artificial Immune System -- Biocomputing
Learning activities and methodology
- Lectures - Practice about Artificial Immune Systems. - Activities directed by the teacher (glossaries, work evaluation, and so on) - Practical assignment - Final Project (Oral presentation of the student work, report) - Individual tutorials
Assessment System
  • % end-of-term-examination 35
  • % of continuous assessment (assigments, laboratory, practicals...) 65
Basic Bibliography
  • Andrew Adamatzky. Advances in Unconventional Computing : Volume 2: Prototypes, Models and Algorithms. Springer. 2016
  • Andrew Adamatzky. Advances in Unconventional Computing: Volume 1: Theory. Springer. 2016
  • Anirban Pathak. Elements of quantum computation and quantum communication. CRC Press . 2013
  • Martyn Amos. Theoretical and experimental DNA computation. Springer. 2005
  • Oliver Morsch. Quantum bits and quantum secrets : how quantum physics is revolutionizing codes and computers. Weinheim : Wiley-VCH. 2008
  • Riley T. Perry. The Temple of Quantum Computing . Riley Perry. 2010
Additional Bibliography
  • Dionisios N. Sotiropoulos, George A. Tsihrintzis. Machine Learning Paradigms: Artificial Immune Systems and their Applications in Software Personalization. Springer. 2017
  • Leandro Castro Jonathan Timmis . Artificial immune systems : a new computational intelligence approach. Springer. 2002

The course syllabus and the academic weekly planning may change due academic events or other reasons.