The past decades have seen an exponential growth in digital electronic computing. But as Moore's Law turns to stagnation, focus turns (back) to alternative approaches to data processing: such as analog computing or cellular computing and also quantum computing.

In this experimental course we survey and look into these and other “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'

Absences: 4 “spontaneous” absences, plus any reasonable pre-excused absences

0. Introduction (PPT, PDF)
1. Conventional Computing (PPT, PDF)
2. Asymptotic Computing (PPT, PDF)
3. Analog Computing (PPT, PDF)
4. Quantum Computing (PPT, PDF)
5. Cellular Automata
6. Swarm Computing
7ff. Student presentations:

• Artificial Chemistry + Reaction-Diffusion + Membrane + P Computing (4x)
• DNA+Molecular+Bacterial+Cellular Computing (4x)
• 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
• http://youtube.com/playlist?list=PLvcvykdwsGNFI1Gz-z4CZXZAtrIdEWTS6