Course detail

Evolutionary and Unconventional Hardware

FIT-EUDAcad. year: 2018/2019

This course introduces computational models and computers which have appeared at the intersection of hardware and artificial intelligence in the recent years as an attempt to solve traditionally hard computational problems. The course surveys relevant theoretical models, reconfigurable architectures and computational intelligence techniques inspired at the levels of phylogeny, ontogeny and epigenesis. In particular, the following topics will be discussed: evolutionary design, evolvable hardware, embryonic electronics, neural hardware, DNA computing and nanotechnology. Typical applications will illustrate the mentioned approaches.

Language of instruction

Czech, English

Mode of study

Not applicable.

Guarantor

prof. Ing. Lukáš Sekanina, Ph.D.

Department

Department of Computer Systems (UPSY)

Learning outcomes of the course unit

Students will be able to utilize evolutionary algorithms to design electronic circuits. They will be able to model, simulate and implement non-conventional, in particular bio-inspired, computational systems.
Understanding the relation between computers (computing) and some natural processes.

Prerequisites

Not applicable.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Not applicable.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

To understand the principles of bio-inspired and unconventional computational systems. To be able to use the bio-inspired and other unconventional techniques in the phase of design, implementation and runtime of a computational device.

Specification of controlled education, way of implementation and compensation for absences

Elaboration and presentation of a project.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

Floreano, D., Mattiussi, C.: Bioinspired Artificial Intelligence: Theories, Methods, and Technologies. The MIT Press, Cambridge 2008, ISBN 978-0-262-06271-8
Greenwood, G., Tyrrell, A.: Introduction to Evolvable Hardware. A Practical Guide for Designing Self-Adaptive Systems. IEEE Press Series on Computational Intelligence, 2006, ISBN 0-471-71977-3
Higuchi, T., Liu, Y., Yao, X.: Evolvable Hardware. Springer Verlag, 2006, ISBN: 0-387-24386-0
Mařík et al.: Umělá inteligence IV, Academia, 2003, 480 s., ISBN 80-200-1044-0
Sekanina L., Vašíček Z., Růžička R., Bidlo M., Jaroš J., Švenda P.: Evoluční hardware: Od automatického generování patentovatelných invencí k sebemodifikujícím se strojům (http://www.academia.cz/evolucni-hardware.html). Academia Praha 2009, ISBN 978-80-200-1729-1

Classification of course in study plans

  • Programme CSE-PHD-4 Doctoral

    branch DVI4 , 0 year of study, summer semester, elective

  • Programme CSE-PHD-4 Doctoral

    branch DVI4 , 0 year of study, summer semester, elective

  • Programme CSE-PHD-4 Doctoral

    branch DVI4 , 0 year of study, summer semester, elective

  • Programme CSE-PHD-4 Doctoral

    branch DVI4 , 0 year of study, summer semester, elective

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

prof. Ing. Lukáš Sekanina, Ph.D.

Syllabus

  1. Introduction: Traditional models of computation, their limits and super-Turing computing
  2. Computer hardware, implementation limits
  3. Natural computing: inspiration, computational platforms, classification
  4. Reconfigurable devices
  5. Cartesian genetic programming
  6. Evolutionary design of digital circuits
  7. Evolvable hardware
  8. Computational development, cellular automata, L-systems
  9. Embryonal electronics
  10. Neural hardware
  11. Nanotechnology and molecular electronics
  12. DNA computing
  13. Recent trends

Guided consultation in combined form of studies

26 hod., optionally

Teacher / Lecturer

prof. Ing. Lukáš Sekanina, Ph.D.