The past decades have seen an exponential growth in digital computing, captured by Moore's Law. This has arguably left a blind spot on alternative approaches to data processing.

In this experimental course we survey, and look into, some of these “unconventional” computing paradigms.

Teacher: Martin Ziegler (use only this email address!)

Location: online

Schedule: Thursdays+Fridays, 14h30 to 16h00 KST

Language: English only (except for students discussing in KLMS)

Prerequisites: CS204 Discrete Mathematics and CS300 Introduction to Algorithms

Preferred: additional background in (one of) Physics OR Chemistry OR Biology or CS322 or CS422

Grading: S/U, students must get assigned and, after the Midterm, present (40~60min) one topic from the textbook 'Unconventional Computing'

1. Conventional Computing
2. Analog Computing
3. Quantum Computing
4. Cellular Automata
5. Molecular Computing
6. DNA Computing
7. Swarm Computing
8. Optical Computing
9. Fluidics
MIDTERM
10.~20: Student presentations:

• Artificial Chemistry + Reaction-Diffusion + Membrane + P Computing (MSc+4xBSc)
• DNA+Molecular+Bacterial+Cellular Computing (MSc+4xBSc)
• Slime Mold Computing
• Reservoir Computing
• Amorphous Computing
• Social Algorithms
• Inductive Turing Machines (requires CS422!)
• Unconventional Problems

• https://en.wikipedia.org/wiki/Unconventional_computing
• https://sites.google.com/view/ucnc-2024/conference/previous-conferences
• https://doi.org/10.1038/s41598-020-68834-1
• http://doi.org/10.1007/978-1-4939-6883-1