Unconventional computing


Unconventional computing is computing by any of a wide range of new or unusual methods. It is also known as alternative computing.
The term of "unconventional computation" was coined by Cristian S. Calude and John Casti and used at the "First International Conference on Unconventional Models of Computation", held in Auckland, New Zealand in 1998.

Background

The general theory of computation allows for a variety of models. Historically, however, computing technology first developed using mechanical methods, and eventually evolved into using electronic techniques, which remain the state-of-the-art. Further development may require development of new technologies.

Computational model

Mechanical computing

Historically, mechanical computers were used in industry before the advent of the transistor.
Mechanical computers retain some interest today both in research and as analogue computers. Some mechanical computers have a theoretical or didactic relevance, such as billiard-ball computers or hydraulic ones.
While some are actually simulated, others are not. No attempt is made to build a functioning computer through the mechanical collisions of billiard balls. The domino computer is another theoretically interesting mechanical computing scheme.

Electronic digital computers

Most modern computers are electronic computers with the Von Neumann architecture based on digital electronics, with extensive integration made possible following the invention of the transistor and the scaling of Moore's law.
Unconventional computing is, according to a conference description, "an interdisciplinary research area with the main goal to enrich or go beyond the standard models, such as the Von Neumann computer architecture and the Turing machine, which have dominated computer science for more than half a century". These methods model their computational operations based on non-standard paradigms, and are currently mostly in the research and development stage.
This computing behavior can be "simulated" using the classical silicon-based micro-transistors or solid state computing technologies, but aim to achieve a new kind of computing.

Generic approaches

These are unintuitive and pedagogical examples that a computer can be made out of almost anything.

Physical objects

Reservoir Computing

Reservoir computing is a computational framework in the context of machine learning. The main advantage of this unconventional computation is simple and fast leaning algorithm. Hardware implementation is also possible known as 'physical reservoir computer'.

Tangible computing

Human computing

Physics approaches

Optical computing

Optical computing uses light to compute.

Spintronics

Atomtronics

Fluidics

Quantum computing

Chemistry approaches

Molecular computing

Biochemistry approaches

Peptide computing

DNA computing

Membrane computing

Biological approaches

Neuroscience

Some biological approaches are heavily inspired by the behavior of neurons.

Cellular automata and amorphous computing

Mathematical approaches

Analog computing

Ternary computing

Ternary computing is a type of computing that uses ternary logic.

Reversible computing

Chaos computing

Stochastic computing