Course detail
Bio-Inspired Computers
FIT-BINAcad. year: 2019/2020
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
Number of ECTS credits
Mode of study
Guarantor
Department
Learning outcomes of the course unit
Understanding the relation between computers (computing) and some natural processes.
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Exam prerequisites:
None.
Course curriculum
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
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
Trefzer M., Tyrrell A.M.: Evolvable Hardware - From Practice to Application. Berlin: Springer Verlag, 2015, ISBN 978-3-662-44615-7
Recommended reading
Mařík et al.: Umělá inteligence IV, Academia, 2003, 480 s., ISBN 80-200-1044-0
Classification of course in study plans
- Programme IT-MSC-2 Master's
branch MBI , 1 year of study, summer semester, compulsory
branch MSK , 0 year of study, summer semester, elective
branch MMM , 0 year of study, summer semester, compulsory-optional
branch MBS , 0 year of study, summer semester, elective
branch MPV , 0 year of study, summer semester, compulsory-optional
branch MIS , 0 year of study, summer semester, elective
branch MIN , 0 year of study, summer semester, compulsory-optional
branch MGM , 0 year of study, summer semester, elective - Programme MITAI Master's
specialization NBIO , 0 year of study, summer semester, compulsory
specialization NMAL , 0 year of study, summer semester, compulsory
specialization NSEN , 0 year of study, summer semester, elective
specialization NVIZ , 0 year of study, summer semester, elective
specialization NGRI , 0 year of study, summer semester, elective
specialization NISD , 0 year of study, summer semester, elective
specialization NSEC , 0 year of study, summer semester, elective
specialization NCPS , 0 year of study, summer semester, elective
specialization NHPC , 0 year of study, summer semester, elective
specialization NNET , 0 year of study, summer semester, elective
specialization NVER , 0 year of study, summer semester, elective
specialization NIDE , 0 year of study, summer semester, elective
specialization NEMB , 0 year of study, summer semester, elective
specialization NSPE , 0 year of study, summer semester, elective
specialization NADE , 0 year of study, summer semester, elective
specialization NMAT , 0 year of study, summer semester, elective
specialization NISY , 0 year of study, summer semester, elective
Type of course unit
Lecture
Teacher / Lecturer
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
Teacher / Lecturer
Syllabus
- Evolutionary design of combinational circuits
- Statistical evaluation of experiments with evolutionary design
- Celulární automaty
- Neuropočítače
Project
Teacher / Lecturer
Syllabus