Course details
Bio-Inspired Computers
BIN Acad. year 2007/2008 Summer semester 5 credits
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.
Guarantor
Language of instruction
Completion
Time span
- 26 hrs lectures
- 8 hrs pc labs
- 18 hrs projects
Department
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
Syllabus of lectures
- Introduction, inspiration in biology, natural computing
- Limits of abstract and physical computing
- Reconfigurable computing devices
- Creative evolutionary design
- Cartesian genetic programming
- Evolutionary design of digital circuits
- Evolutionary circuit design, extreme environments
- Evolvable hardware, applications
- Evolution and development
- Embryonic electronics, cellular computational platforms, Cell Matrix, POEtic
- DNA computing
- Nanotechnology and molecular electronics
- Recent trends
Syllabus of computer exercises
- Evolutionary design of combinational circuits
- Virtual reconfigurable circuits
- Celulární automaty
- Cell Matrix
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