An adaptive algorithm is an

algorithm In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing ...

that changes its behavior at the time it is run, based on information available and on ''a priori'' defined reward mechanism (or criterion). Such information could be the story of recently received data, information on the available computational resources, or other run-time acquired (or ''a priori'' known) information related to the environment in which it operates. Among the most used adaptive algorithms is the Widrow-Hoff’s least mean squares (LMS), which represents a class of stochastic gradient-descent algorithms used in adaptive filtering and machine learning. In adaptive filtering the LMS is used to mimic a desired filter by finding the filter coefficients that relate to producing the least mean square of the error signal (difference between the desired and the actual signal). For example, stable partition, using no additional memory is ''O''(''n'' lg ''n'') but given ''O''(''n'') memory, it can be ''O''(''n'') in time. As implemented by the

C++ Standard Library The C standard library or libc is the standard library for the C programming language, as specified in the ISO C standard. ISO/IEC (2018). '' ISO/IEC 9899:2018(E): Programming Languages - C §7'' Starting from the original ANSI C standard, it was ...

stable_partition
is adaptive and so it acquires as much memory as it can get (up to what it would need at most) and applies the algorithm using that available memory. Another example is

adaptive sort A sorting algorithm falls into the adaptive sort family if it takes advantage of existing order in its input. It benefits from the presortedness in the input sequence – or a limited amount of disorder for various definitions of measures of disord ...

, whose behavior changes upon the presortedness of its input. An example of an adaptive algorithm in

radar Radar is a detection system that uses radio waves to determine the distance ('' ranging''), angle, and radial velocity of objects relative to the site. It can be used to detect aircraft, ships, spacecraft, guided missiles, motor vehicles, we ...

systems is the

constant false alarm rate Constant false alarm rate (CFAR) detection refers to a common form of adaptive algorithm used in radar systems to detect target returns against a background of noise, clutter and interference. Principle In the radar receiver, the returning echoes ...

(CFAR) detector. In

machine learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine ...

and

optimization Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfi ...

, many algorithms are adaptive or have adaptive variants, which usually means that the algorithm parameters such as

learning rate In machine learning and statistics, the learning rate is a tuning parameter in an optimization algorithm that determines the step size at each iteration while moving toward a minimum of a loss function. Since it influences to what extent newly ...

are automatically adjusted according to statistics about the optimisation thus far (e.g. the rate of convergence). Examples include

adaptive simulated annealing Adaptive simulated annealing (ASA) is a variant of simulated annealing (SA) algorithm in which the algorithm parameters that control temperature schedule and random step selection are automatically adjusted according to algorithm progress. This mak ...

adaptive coordinate descent Adaptive coordinate descent is an improvement of the coordinate descent algorithm to non-separable optimization by the use of adaptive encoding. The adaptive coordinate descent approach gradually builds a transformation of the coordinate system suc ...

adaptive quadrature Adaptive quadrature is a numerical integration method in which the integral of a function f(x) is approximated using static quadrature rules on adaptively refined subintervals of the region of integration. Generally, adaptive algorithms are just ...

AdaBoost AdaBoost, short for ''Adaptive Boosting'', is a statistical classification meta-algorithm formulated by Yoav Freund and Robert Schapire in 1995, who won the 2003 Gödel Prize for their work. It can be used in conjunction with many other types of ...

Adagrad Stochastic gradient descent (often abbreviated SGD) is an iterative method for optimizing an objective function with suitable smoothness properties (e.g. differentiable or subdifferentiable). It can be regarded as a stochastic approximation of gr ...

, Adadelta, RMSprop, and Adam. In

data compression In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compressio ...

adaptive coding Adaptive coding refers to variants of entropy encoding methods of lossless data compression. They are particularly suited to streaming data, as they adapt to localized changes in the characteristics of the data, and don't require a first pass over ...

algorithms such as

Adaptive Huffman coding Adaptive Huffman coding (also called Dynamic Huffman coding) is an adaptive coding technique based on Huffman coding In computer science and information theory, a Huffman code is a particular type of optimal prefix code that is commonly used fo ...

Prediction by partial matching Prediction by partial matching (PPM) is an adaptive statistical data compression technique based on context modeling and prediction. PPM models use a set of previous symbols in the uncompressed symbol stream to predict the next symbol in the st ...

can take a stream of data as input, and adapt their compression technique based on the symbols that they have already encountered. In

signal processing Signal processing is an electrical engineering subfield that focuses on analyzing, modifying and synthesizing ''signals'', such as sound, images, and scientific measurements. Signal processing techniques are used to optimize transmissions, ...

, the

Adaptive Transform Acoustic Coding Adaptive Transform Acoustic Coding (ATRAC) is a family of proprietary audio compression algorithms developed by Sony. MiniDisc was the first commercial product to incorporate ATRAC in 1992. ATRAC allowed a relatively small disc like MiniDisc to ...

(ATRAC) codec used in MiniDisc recorders is called "adaptive" because the window length (the size of an audio "chunk") can change according to the nature of the sound being compressed, to try to achieve the best-sounding compression strategy.

References

Algorithms {{soft-eng-stub

See also

References