forecasting methods, etc.) to increase the efficiency of model training in order to achieve a synergistic effect from their use and the best results of the work of artificial intelligence systems. One of the ideas that is laid down in the creation of composite artificial intelligence is to obtain a sane artificial intelligence that will be able to understand the essence of the problems and solve a wide range of problems, offering optimal solutions.236,237,238.
Compression is a method of reducing the size of computer files. There are several compression programs available, such as gzip and WinZip239.
Computation is any type of arithmetic or non-arithmetic calculation that follows a well-defined model (e.g., an algorithm)240.
Computational chemistry is a discipline using mathematical methods for the calculation of molecular properties or for the simulation of molecular behaviour. It also includes, e.g., synthesis planning, database searching, combinatorial library manipulation.241,242,243.
Computational complexity theory – focuses on classifying computational problems according to their inherent difficulty, and relating these classes to each other. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of mathematical steps, such as an algorithm244.
Computational creativity (also artificial creativity, mechanical creativity, creative computing, or creative computation) is a multidisciplinary endeavour that includes the fields of artificial intelligence, cognitive psychology, philosophy, and the arts245.
Computational cybernetics is the integration of cybernetics and computational intelligence techniques246.
Computational efficiency of an agent or a trained model is the amount of computational resources required by the agent to solve a problem at the inference stage247.
Computational efficiency of an intelligent system is the amount of computing resources required to train an intelligent system with a certain level of performance on a given volume of tasks248.
Computational Graphics Processing Unit (computational GPU, cGPU) – graphic processor-computer, GPU-computer, multi-core GPU used in hybrid supercomputers to perform parallel mathematical calculations; for example, one of the first GPUs in this category contains more than 3 billion transistors – 512 CUDA cores and up to 6 GB of memory249.
Computational humor is a branch of computational linguistics and artificial intelligence which uses computers in humor research250.
Computational intelligence (CI) usually refers to the ability of a computer to learn a specific task from data or experimental observation251.
Computational learning theory (COLT) in computer science, is a subfield of artificial intelligence devoted to studying the design and analysis of machine learning algorithms252.
Computational linguistics is an interdisciplinary field concerned with the statistical or rule-based modeling of natural language from a computational perspective, as well as the study of appropriate computational approaches to linguistic questions253.
Computational mathematics is the mathematical research in areas of science where computing plays an essential role254.
Computational neuroscience (also known as theoretical neuroscience or mathematical neuroscience) is a branch of neuroscience which employs mathematical models, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology, and cognitive abilities of the nervous system255,256.
Computational number theory (also algorithmic number theory) – the study of algorithms for performing number theoretic computations257,,258.
Computational problem in theoretical computer science is a mathematical object representing a collection of questions that computers might be able to solve259.
Computational statistics (or statistical computing) is the application of computer science and software engineering principles to solving scientific problems. It involves the use of computing hardware, networking, algorithms, programming, databases and other domain-specific knowledge to design simulations of physical phenomena to run on computers. Computational science crosses disciplines and can even involve the humanities260,261.
Computer engineering — technologies for digital modeling and design of objects and production processes throughout the life cycle262.
Computer incident is a fact of violation and (or) cessation of the operation of a critical information infrastructure object, a telecommunication network used to organize the interaction of such objects, and (or) a violation of the security of information processed by such an object, including as a result of a computer attack263.
Computer science – the theory, experimentation, and engineering that form the basis for the design and use of computers. It involves the study of algorithms that process, store, and communicate digital information. A computer scientist specializes in the theory of computation and the design of computational systems. Computer science is the study of computation, automation, and information. Computer science spans theoretical disciplines (such as algorithms, theory of computation, and information theory) to practical disciplines (including the design and implementation of hardware and software). Computer science is generally considered an area of academic research and distinct from computer programming264.
Computer simulation is the process of mathematical modelling, performed on a computer, which is designed to predict the behaviour of, or the outcome of, a real-world or physical system. The reliability of some mathematical models can be determined by comparing their results to the real-world outcomes they aim to predict. Computer simulations have become a useful tool for the mathematical modeling of many natural systems in physics (computational physics), astrophysics, climatology, chemistry, biology and manufacturing, as well as human systems in economics, psychology, social science, health care and engineering