Course details

Bio-Inspired Computers

BIN Acad. year 2017/2018 Summer semester 5 credits

Current academic year

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, cellular systems, embryonal and neural hardware, molecular computers and nanotechnology. Typical applications will illustrate the mentioned approaches.

Guarantor

Sekanina Lukáš, prof. Ing., Ph.D. (DCSY)

Language of instruction

Czech

Completion

Examination (written)

Time span

  • 26 hrs lectures
  • 8 hrs pc labs
  • 18 hrs projects

Assessment points

  • 52 pts final exam (written part)
  • 15 pts mid-term test (written part)
  • 8 pts labs
  • 25 pts projects

Department

Department of Computer Systems (UPSY)

Subject specific learning outcomes and competences

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.

Learning objectives

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

Prerequisite knowledge and skills

There are no prerequisites

Fundamental literature

  • 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
  • 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
  • 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

Syllabus of lectures

  1. Introduction, inspiration in biology, entropy and self-organization
  2. Limits of abstract and physical computing
  3. Evolutionary design
  4. Cartesian genetic programming
  5. Reconfigurable computing devices
  6. Evolutionary design of digital circuits
  7. Evolutionary circuit design, extreme environments
  8. Evolvable hardware, applications
  9. Computational development
  10. Embryonal and neural hardware
  11. DNA computing
  12. Nanotechnology and molecular electronics
  13. Recent trends

Syllabus of computer exercises

  1. Evolutionary design of combinational circuits
  2. Statistical evaluation of experiments with evolutionary design
  3. Virtual reconfigurable circuits
  4. Celulární automaty

Progress assessment

Study evaluation is based on marks obtained for specified items. Minimimum number of marks to pass is 50.

None

Controlled instruction

Mid-term exam, project, computer labs assignments. 

Course inclusion in study plans

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