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.
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.
Reservoir computing.
Reservoir computing is a computational framework in the context of machine learning. The main advantage of this unconventional computing framework is that it facilitates a simple and fast learning algorithm in addition to a hardware implementation, known as a physical reservoir computer.
Physics approaches.
Optical computing.
Optical computing uses light to compute.
Biological approaches.
Neuroscience.
Some biological approaches are heavily inspired by the behavior of neurons.
Mathematical approaches.
Ternary computing.
Ternary computing is a type of computing that uses ternary logic (instead of binary logic).