Title:

Bio-Inspired Computers

Code:BIN
Ac.Year:2012/2013
Term:Summer
Study plans:
ProgramBranchYearDuty
IT-MSC-2MBI1stCompulsory
IT-MSC-2MBS-Elective
IT-MSC-2MGM-Elective
IT-MSC-2MIN-Compulsory-Elective - group I
IT-MSC-2MIS-Elective
IT-MSC-2MMI-Elective
IT-MSC-2MMM-Compulsory-Elective - group N
IT-MSC-2MPV1stCompulsory-Elective - group B
IT-MSC-2MSK-Elective
IT-MSC-2EITE2ndElective
Language:Czech
Private info:http://www.fit.vutbr.cz/study/courses/BIN/private/
Credits:5
Completion:examination (written)
Type of
instruction:
Hour/semLecturesSem. ExercisesLab. exercisesComp. exercisesOther
Hours:2600818
 ExaminationTestsExercisesLaboratoriesOther
Points:60150817
Guarantee:Sekanina Lukáš, prof. Ing., Ph.D., DCSY
Lecturer:Sekanina Lukáš, prof. Ing., Ph.D., DCSY
Instructor:Bidlo Michal, Ing., Ph.D., DCSY
Petrlík Jiří, Ing., DCSY
Vašíček Zdeněk, Ing., Ph.D., DCSY
Faculty:Faculty of Information Technology BUT
Department:Department of Computer Systems FIT BUT
Schedule:
DayLessonWeekRoomStartEndLect.Gr.St.G.EndG.
Thuexam - řádný termín2013-05-16G20210:0011:501MIT
Thuexam - řádný termín2013-05-16G20210:0011:502MIT
Thuexam - 1. opravný termín2013-05-30E10410:0011:501MIT
Thuexam - 1. opravný termín2013-05-30E10410:0011:502MIT
Friexam - 2. opravný termín2013-06-07A11310:0011:502MIT
Friexam - 2. opravný termín2013-06-07A11310:0011:501MIT
 
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.
Description:
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, embryonic hardware, molecular computers and nanotechnology. Typical applications will illustrate the mentioned approaches.
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.
Generic learning outcomes and competences:
Understanding the relation between computers (computing) and some natural processes.
Syllabus of lectures:
  1. Introduction, inspiration in biology, natural computing
  2. Limits of abstract and physical computing
  3. Reconfigurable computing devices
  4. Creative evolutionary design
  5. Cartesian genetic programming
  6. Evolutionary design of digital circuits
  7. Evolutionary circuit design, extreme environments
  8. Evolvable hardware, applications
  9. Evolution and development
  10. Embryonic electronics, cellular computational platforms, Cell Matrix
  11. DNA computing
  12. Nanotechnology and molecular electronics
  13. Recent trends
Syllabus of computer exercises:
  1. Evolutionary design of combinational circuits
  2. Virtual reconfigurable circuits
  3. Celulární automaty
  4. Cell Matrix

 

Syllabus - others, projects and individual work of students:
A project will be assigned to each student. Implementation, presentation and documentation of the project will be evaluated.
Fundamental literature:
  1. 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 
  2. Floreano, D., Mattiussi, C.: Bioinspired Artificial Intelligence: Theories, Methods, and Technologies. The MIT Press, Cambridge 2008, ISBN 978-0-262-06271-8
  3. 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
  4. Higuchi, T., Liu, Y., Yao, X.: Evolvable Hardware. Springer Verlag, 2006, ISBN: 0-387-24386-0
  5. Zebulum, R., Pacheco, M., Vellasco, M.: Evolutionary Electronics - Automatic Design of Electronic Circuits and Systems by Genetic Algorithms. CRC Press, Boca Raton, 2002, 299 s., ISBN 0-8493-0865-8
  6. Sipper, M.: Evolution of Parallel Cellular Machines - The Cellular Programming Approach. LNCS 1194, Springer, 1997, 198 s., ISBN 3-540-62613-1
Study literature:
  1. 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
  2. Floreano, D., Mattiussi, C.: Bioinspired Artificial Intelligence: Theories, Methods, and Technologies. The MIT Press, Cambridge 2008, ISBN 978-0-262-06271-8
  3. Higuchi, T., Liu, Y., Yao, X.: Evolvable Hardware. Springer Verlag, 2006, ISBN: 0-387-24386-0
  4. Zebulum, R., Pacheco, M., Vellasco, M.: Evolutionary Electronics - Automatic Design of Electronic Circuits and Systems by Genetic Algorithms. CRC Press, Boca Raton, 2002, 299 p., ISBN 0-8493-0865-8
Progress assessment:
Mid-term exam, project, computer labs assignments. 
Exam prerequisites:
None