Unconventional computing

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Thematic areas of unconventional computing

Unconventional computing is computing by any of a wide range of new or unusual methods. It is also known as alternative computing.

Contents

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", [1] held in Auckland, New Zealand in 1998. [2]

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.[ why? ]

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, while hydraulic ones like the MONIAC or the Water integrator were used effectively. [3]

While some are actually simulated, others are not[ clarification needed ]. No attempt is made[ dubious ] to build a functioning computer through the mechanical collisions of billiard balls. The domino computer is another theoretically interesting mechanical computing scheme.[ why? ]

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[ which? ] conference description, [4] "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"[ clarification needed ] 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 computing framework is that it facilitates a simple and fast learning algorithm in addition to a hardware implementation, known as a 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 (instead of binary logic).

Reversible computing

Chaos computing

Stochastic computing

See also

Related Research Articles

Analog computer Computer that uses continuously variable technology

An analog computer or analogue computer is a type of computer that uses the continuously variable aspects of physical phenomena such as electrical, mechanical, or hydraulic quantities to model the problem being solved. In contrast, digital computers represent varying quantities symbolically and by discrete values of both time and amplitude.

Computing Branch of knowledge

Computing is any goal-oriented activity requiring, benefiting from, or creating computing machinery. It includes the study and experimentation of algorithmic processes and development of both hardware and software. It has scientific, engineering, mathematical, technological and social aspects. Major computing disciplines include computer engineering, computer science, cybersecurity, data science, information systems, information technology and software engineering.

Central processing unit Central component of any computer system which executes input/output, arithmetical, and logical operations

A central processing unit (CPU), also called a central processor, main processor or just processor, is the electronic circuitry that executes instructions comprising a computer program. The CPU performs basic arithmetic, logic, controlling, and input/output (I/O) operations specified by the instructions in the program. This contrasts with external components such as main memory and I/O circuitry, and specialized processors such as graphics processing units (GPUs).

Computer science Study of the foundations and applications of computation

Computer science is the study of algorithmic processes, computational machines and computation itself. As a discipline, computer science spans a range of topics from theoretical studies of algorithms, computation and information to the practical issues of implementing computational systems in hardware and software.

History of computing hardware From early calculation aids to modern day computers

The history of computing hardware covers the developments from early simple devices to aid calculation to modern day computers. Before the 20th century, most calculations were done by humans. Early mechanical tools to help humans with digital calculations, like the abacus, were referred to as calculating machines or calculators. The machine operator was called the computer.

Theoretical computer science Subfield of computer science and mathematics

Theoretical computer science (TCS) is a subset of general computer science and mathematics that focuses on mathematical aspects of computer science such as the theory of computation, lambda calculus, and type theory.

History of computing

The history of computing is longer than the history of computing hardware and modern computing technology and includes the history of methods intended for pen and paper or for chalk and slate, with or without the aid of tables.

Neuromorphic engineering, also known as neuromorphic computing, is the use of very-large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures present in the nervous system. A neuromorphic computer/chip is any device that uses physical artificial neurons to do computations. In recent times, the term neuromorphic has been used to describe analog, digital, mixed-mode analog/digital VLSI, and software systems that implement models of neural systems. The implementation of neuromorphic computing on the hardware level can be realized by oxide-based memristors, spintronic memories, threshold switches, and transistors.

Fluidics

Fluidics, or fluidic logic, is the use of a fluid to perform analog or digital operations similar to those performed with electronics.

An integrator in measurement and control applications is an element whose output signal is the time integral of its input signal. It accumulates the input quantity over a defined time to produce a representative output.

Computational science, also known as scientific computing or scientific computation (SC), is a rapidly growing field that uses advanced computing capabilities to understand and solve complex problems. It is an area of science which spans many disciplines, but at its core, it involves the development of models and simulations to understand natural systems.

Reversible computing is any model of computation where the computational process to some extent is time-reversible. In a model of computation that uses deterministic transitions from one state of the abstract machine to another, a necessary condition for reversibility is that the relation of the mapping from states to their successors must be one-to-one. Reversible computing is a form of unconventional computing.

A chemical computer, also called a reaction-diffusion computer, Belousov–Zhabotinsky (BZ) computer, or gooware computer, is an unconventional computer based on a semi-solid chemical "soup" where data are represented by varying concentrations of chemicals. The computations are performed by naturally occurring chemical reactions.

Billiard-ball computer Type of conservative logic circuit

A billiard-ball computer, a type of conservative logic circuit, is an idealized model of a reversible mechanical computer based on Newtonian dynamics, proposed in 1982 by Edward Fredkin and Tommaso Toffoli. Instead of using electronic signals like a conventional computer, it relies on the motion of spherical billiard balls in a friction-free environment made of buffers against which the balls bounce perfectly. It was devised to investigate the relation between computation and reversible processes in physics.

The idea of human artifacts being given life has fascinated humankind for at least 3000 years. As seen in tales ranging from Pygmalion to Frankenstein, humanity has long been intrigued by the concept of artificial life.

Computer Automatic general-purpose device for performing arithmetic or logical operations

A computer is a machine that can be programmed to carry out sequences of arithmetic or logical operations automatically. Modern computers can perform generic sets of operations known as programs. These programs enable computers to perform a wide range of tasks. A computer system is a "complete" computer that includes the hardware, operating system, and peripheral equipment needed and used for "full" operation. This term may also refer to a group of computers that are linked and function together, such as a computer network or computer cluster.

Mechanical computer Computer built from mechanical components such as levers and gears

A mechanical computer is built from mechanical components such as levers and gears, rather than electronic components. The most common examples are adding machines and mechanical counters, which use the turning of gears to increment output displays. More complex examples could carry out multiplication and division—Friden used a moving head which paused at each column—and even differential analysis. One model sold in the 1960s calculated square roots.

Lateral computing is a lateral thinking approach to solving computing problems. Lateral thinking has been made popular by Edward de Bono. This thinking technique is applied to generate creative ideas and solve problems. Similarly, by applying lateral-computing techniques to a problem, it can become much easier to arrive at a computationally inexpensive, easy to implement, efficient, innovative or unconventional solution.

Digital electronic computer

In computer science, a digital electronic computer is a computer machine which is both an electronic computer and a digital computer. Examples of a digital electronic computers include the IBM PC, the Apple Macintosh as well as modern smartphones. When computers that were both digital and electronic appeared, they displaced almost all other kinds of computers, but computation has historically been performed in various non-digital and non-electronic ways: the Lehmer sieve is an example of a digital non-electronic computer, while analog computers are examples of non-digital computers which can be electronic, and mechanical computers are examples of non-electronic computers. An example of a computer which is both non-digital and non-electronic is the ancient Antikythera mechanism found in Greece. All kinds of computers, whether they are digital or analog, and electronic or non-electronic, can be Turing complete if they have sufficient memory. A digital electronic computer is not necessarily a programmable computer, a stored program computer, or a general purpose computer, since in essence a digital electronic computer can be built for one specific application and be non-reprogrammable. As of 2014, most personal computers and smartphones in people's homes that use multicore central processing units are also parallel computers using the MIMD paradigm, a technology previously only used in digital electronic supercomputers. As of 2014, most digital electronic supercomputers are also cluster computers, a technology that can be used at home in the form of small Beowulf clusters. Parallel computation is also possible with non-digital or non-electronic computers. An example of a parallel computation system using the abacus would be a group of human computers using a number of abacus machines for computation and communicating using natural language.

This glossary of artificial intelligence is a list of definitions of terms and concepts relevant to the study of artificial intelligence, its sub-disciplines, and related fields. Related glossaries include Glossary of computer science, Glossary of robotics, and Glossary of machine vision.

References

  1. "Unconventional Models of Computation 1998".
  2. C.S. Calude. "Unconventional Computing: A Brief Subjective History, CDMTCS Report 480, 2015".
  3. Penrose, Roger: The Emperor's New Mind. Oxford University Press, 1990. See also corresponding article on it.
  4. "Unconventional computation Conference 2007".