Course detail

Bio-Inspired Computers

FIT-BINAcad. year: 2021/2022

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 computational and energy inefficiency of conventional computers. 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: emergence and self-organization, evolutionary design, evolvable hardware, cellular systems, neural hardware, molecular computers and nanotechnology. Typical applications will illustrate the mentioned approaches.

Language of instruction

Czech

Number of ECTS credits

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 computational structures and 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

Mid-term exam, project and its presentation, computer lab assignments.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

To understand the principles of bio-inspired computational systems. To be able to use the bio-inspired techniques in the design, implementation and operational phases of a computational system.

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

Mid-term exam, realization and presentation of the project, computer lab assignments in due dates. The minimal number of points which can be obtained from the final exam is 20. Otherwise, no points will be assigned to a student. In the case of a reported barrier preventing the student to defend the project or solve a lab assignment, the student will be allowed to defend the project or solve the lab assignment on an alternative date.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Floreano D., Mattiussi C.: Bioinspired Artificial Intelligence: Theories, Methods, and Technologies. The MIT Press, Cambridge 2008, ISBN 978-0-262-06271-8
Miller J.F.: Cartesian Genetic Programming, Springer Verlag, 2011, ISBN 978-3-642-17309-7
Rozenberg G., Bäck T., Kok J.N.: Handbook of Natural Computing, Springer 2012, 2052 p., ISBN 978-3540929093
Sekanina L., Vašíček Z., Růžička R., Bidlo M., Jaroš J., Švenda P.: Evoluční hardware: Od automatického generování patentovatelných invencí k sebemodifikujícím se strojům. Academia Praha 2009, ISBN 978-80-200-1729-1
Sze V., Chen Y.H., Yang T.J., Emer J.S.: Efficient Processing of Deep Neural Networks. Morgan & Claypool Publishers, 2020, ISBN 978-1681738352
Trefzer M., Tyrrell A.M.: Evolvable Hardware - From Practice to Application. Berlin: Springer Verlag, 2015, ISBN 978-3-662-44615-7

Type of course unit

Lecture

26 hod., optionally

Teacher / Lecturer

prof. Ing. Lukáš Sekanina, Ph.D.
doc. Ing. Michal Bidlo, Ph.D.

Syllabus

Introduction, inspiration in biology, entropy and self-organization
Limits of abstract and physical computing
Evolutionary design
Cartesian genetic programming
Reconfigurable computing devices
Evolutionary design of electronic circuits
Evolvable hardware, applications
Computational development
Neural networks and neuroevolution
Neural hardware
DNA computing
Nanotechnology and molecular electronics
Recent trends

Exercise in computer lab

8 hod., compulsory

Teacher / Lecturer

Ing. Jakub Husa
Ing. Vojtěch Mrázek, Ph.D.
doc. Ing. Zdeněk Vašíček, Ph.D.

Syllabus

Evolutionary design of combinational circuits
Statistical evaluation of experiments with evolutionary design
Celulární automaty
Neuropočítače

Project

18 hod., compulsory

Teacher / Lecturer

Ing. Jakub Husa
doc. Ing. Zdeněk Vašíček, Ph.D.
Ing. Vojtěch Mrázek, Ph.D.
prof. Ing. Lukáš Sekanina, Ph.D.

Syllabus

Every student will choose one project from a list of approved projects that are relevant for this course. The implementation, presentation and documentation of the project will be evaluated.

Elearning

eLearning: currently opened course

VUT

Faculties

University Institutes

Parts

Bio-Inspired Computers

Type of course unit