Александр Чесалов – Глоссариум по искусственному интеллекту: 2500 терминов. Том 2 (страница 14)
Decision intelligence is a discipline offers a framework to assist data and analytics practitioners develop, model, align, implement, track, and modify decision models and processes related to business results and performance353.
Decision support system (DSS) is an information system that supports business or organizational decision-making activities. DSSs serve the management, operations and planning levels of an organization (usually mid and higher management) and help people make decisions about problems that may be rapidly changing and not easily specified in advance – i.e., unstructured and semi-structured decision problems. Decision support systems can be either fully computerized or human-powered, or a combination of both354.
Decision theory (also theory of choice) – the study of the reasoning underlying an agent’s choices. Decision theory can be broken into two branches: normative decision theory, which gives advice on how to make the best decisions given a set of uncertain beliefs and a set of values, and descriptive decision theory which analyzes how existing, possibly irrational agents actually make decisions355.
Decision threshold this indicator allows you to define the cut-off point for classifying observations. Observations with predicted values greater than the classification cutoff are classified as positive, and those with predicted values less than the cutoff are classified as negative356.
Decision tree is a tree-and-branch model used to represent decisions and their possible consequences, similar to a flowchart357.
Decision tree learning – uses a decision tree (as a predictive model) to go from observations about an item (represented in the branches) to conclusions about the item’s target value (represented in the leaves). It is one of the predictive modeling approaches used in statistics, data mining and machine learning358.
Decision Tree uses tree-like graph or model as a structure to perform decision analysis. It uses each node to represent a test on an attribute, each branch to represent the outcome of the test, and each leaf node to represent a class label359,360,361.
Declarative programming is a programming paradigm – a style of building the structure and elements of computer programs – that expresses the logic of a computation without describing its control flow362,363.
Decoder in general, any ML system that converts from a processed, dense, or internal representation to a more raw, sparse, or external representation. Decoders are often a component of a larger model, where they are frequently paired with an encoder. In sequence-to-sequence tasks, a decoder starts with the internal state generated by the encoder to predict the next sequence. Refer to Transformer for the definition of a decoder within the Transformer architecture364.
Decompression – used to restore data to uncompressed form after compression365.
Deductive classifier is a type of artificial intelligence inference engine. It takes as input a set of declarations in a frame language about a domain such as medical research or molecular biology366.
Deductive Reasoning, also known as logical deduction, is a reasoning method that relies on premises to reach a logical conclusion. It works in a top- down manner, in which the final conclusion is obtained by reducing the general rules that hold the entire domain until only the conclusion is left367.
Deep Blue was a chess supercomputer developed by IBM. It was the first computer chess player that beat the world cham- pion Garry Kasparov, after six-game match in 1997368.
Deep Learning (DL) is a subfield of machine learning concerned with algorithms that are inspired by the human brain that works in a hierarchical way. Deep Learning models, which are mostly based on the (artificial) neural networks, have been applied to different fields, such as speech recognition, computer vision, and natural language processing369.
Deep model is a type of neural network containing multiple hidden layers. Contrast with wide model370.
Deep neural network is a multilayer network containing several (many) hidden layers of neurons between the input and output layers, which allows modeling complex nonlinear relationships. GNNs are now increasingly used to solve such artificial intelligence problems as speech recognition, natural language processing, computer vision, etc., including in robotics371.
Deep Q-Network (DQN) in Q-learning, is a deep neural network that predicts Q-functions. Critic is a synonym for Deep Q-Network372.
DeepMind is an artificial intelligence company founded in 2010 and later acquired by Google in 2014. DeepMind developed
Default logic is a non-monotonic logic proposed by Raymond Reiter to formalize reasoning with default assumptions375.
Degree of maturity is the degree of clarity (clarity) of the definition, management, measurement, control and implementation of a specific technological process376.
Demographic parity is a fairness metric that is satisfied if the results of a model’s classification are not dependent on a given sensitive attribute377.
Denoising it is the task of machine vision to remove noise from an image. It is a common supervised learning approach in which noise is artificially added to the dataset and the system removes it on its own378.
Dense feature is a feature in which most values are non-zero, typically a Tensor of floating-point values. Contrast with sparse feature379.
Dense layer – synonym for fully connected layer380.
Depersonalization of personal data – actions, as a result of which it becomes impossible, without the use of additional information, to determine the ownership of personal data by a specific subject of personal data381,382.
Depth – the number of layers (including any embedding layers) in a neural network that learn weights. For example, a neural network with 5 hidden layers and 1 output layer has a depth of 6383.
Depthwise separable convolutional neural network (sepCNN) is a convolutional neural network architecture based on Inception, but where Inception modules are replaced with depthwise separable convolutions. Also known as Xception. A depthwise separable convolution (also abbreviated as separable convolution) factors a standard 3-D convolution into two separate convolution operations that are more computationally efficient: first, a depthwise convolution, with a depth of 1 (n ✕ n ✕ 1), and then second, a pointwise convolution, with length and width of 1 (1 ✕ 1 ✕ n). To learn more, see Xception: Deep Learning with Depthwise Separable Convolutions384.
Description logic is a family of formal knowledge representation languages. Many DLs are more expressive than propositional logic but less expressive than first-order logic. In contrast to the latter, the core reasoning problems for DLs are (usually) decidable, and efficient decision procedures have been designed and implemented for these problems. There are general, spatial, temporal, spatiotemporal, and fuzzy descriptions logics, and each description logic features a different balance between DL expressivity and reasoning complexity by supporting different sets of mathematical constructors385.
Design Center is an organizational unit (the entire organization or its subdivision) that performs a full range or part of the work on creating products up to the stage of its mass production, and also has the necessary personnel, equipment and technologies for this386.
Developmental robotics (DevRob) (also epigenetic robotics) is a scientific field which aims at studying the developmental mechanisms, architectures, and constraints that allow lifelong and open-ended learning of new skills and new knowledge in embodied machines387.
Device is a category of hardware that can run a TensorFlow session, including CPUs, GPUs, and TPUs388.
DevOps (development & operations) is a set of practices, tools, and culture philosophies that automate and integrate the processes of software development teams and IT teams. DevOps emphasizes team empowerment, collaboration and collaboration, and technology automation. The term DevOps is also understood as a special approach to organizing development teams. Its essence is that developers, testers and administrators work in a single thread – they are not each responsible for their own stage, but work together on the release of the product and try to automate the tasks of their departments so that the code moves between stages without delay. In DevOps, responsibility for the result is distributed among the entire team389,390.
Diagnosis concerned with the development of algorithms and techniques that are able to determine whether the behaviour of a system is correct. If the system is not functioning correctly, the algorithm should be able to determine, as accurately as possible, which part of the system is failing, and which kind of fault it is facing. The computation is based on observations, which provide information on the current behaviour391.