Course detail
Bio-Inspired Computers
FIT-BINAcad. year: 2020/2021
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.
Supervisor
Department
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.
Recommended optional programme components
Not applicable.
Recommended or required reading
Rozenberg G., Bäck T., Kok J.N.: Handbook of Natural Computing, Springer 2012, 2052 p., ISBN 978-3540929093.
Kvasnička, V., Pospíchal J., Tiňo P.: Evolučné algoritmy. Vydavatelství STU Bratislava, 2000, 215 s., ISBN 80-227-1377-5. (in Czech)
Mařík et al.: Umělá inteligence IV, Academia, 2003, 480 s., ISBN 80-200-1044-0. (in Czech).
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. (in Czech)
Floreano, D., Mattiussi, C.: Bioinspired Artificial Intelligence: Theories, Methods, and Technologies. The MIT Press, Cambridge 2008, ISBN 978-0-262-06271-8.
Trefzer M., Tyrrell A.M.: Evolvable Hardware - From Practice to Application. Berlin: Springer Verlag, 2015, ISBN 978-3-662-44615-7.
Rozenberg G., Bäck T., Kok J.N.: Handbook of Natural Computing, Springer 2012, 2052 p., ISBN 978-3540929093Miller J.F.: Cartesian Genetic Programming, Springer Verlag 2011, ISBN 978-3-642-17309-7.
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.
Exam prerequisites:
None.
Language of instruction
Czech
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.
Classification of course in study plans
- Programme IT-MGR-2 Master's
branch MPV , any year of study, summer semester, 5 credits, compulsory-optional
branch MGM , any year of study, summer semester, 5 credits, elective
branch MSK , any year of study, summer semester, 5 credits, elective
branch MIS , any year of study, summer semester, 5 credits, elective
branch MBS , any year of study, summer semester, 5 credits, elective
branch MIN , any year of study, summer semester, 5 credits, compulsory-optional
branch MMM , any year of study, summer semester, 5 credits, compulsory-optional - Programme MITAI Master's
specialization NADE , any year of study, summer semester, 5 credits, elective
specialization NBIO , any year of study, summer semester, 5 credits, compulsory
specialization NGRI , any year of study, summer semester, 5 credits, elective
specialization NNET , any year of study, summer semester, 5 credits, elective
specialization NVIZ , any year of study, summer semester, 5 credits, elective
specialization NCPS , any year of study, summer semester, 5 credits, elective
specialization NSEC , any year of study, summer semester, 5 credits, elective
specialization NEMB , any year of study, summer semester, 5 credits, elective
specialization NHPC , any year of study, summer semester, 5 credits, elective
specialization NISD , any year of study, summer semester, 5 credits, elective
specialization NIDE , any year of study, summer semester, 5 credits, elective
specialization NISY , any year of study, summer semester, 5 credits, elective
specialization NMAL , any year of study, summer semester, 5 credits, compulsory
specialization NMAT , any year of study, summer semester, 5 credits, elective
specialization NSEN , any year of study, summer semester, 5 credits, elective
specialization NVER , any year of study, summer semester, 5 credits, elective
specialization NSPE , any year of study, summer semester, 5 credits, elective - Programme IT-MGR-2 Master's
branch MBI , 1. year of study, summer semester, 5 credits, compulsory
Type of course unit
Lecture
26 hours, optionally
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
8 hours, compulsory
Teacher / Lecturer
Syllabus
- Evolutionary design of combinational circuits
- Statistical evaluation of experiments with evolutionary design
- Celulární automaty
- Neuropočítače
Project
18 hours, compulsory
Teacher / Lecturer
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.