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This article updates the problem of professional training of the future teacher in the context of rethinking the education process, forming a system of knowledge, abilities and skills necessary for the professional compe...

Recently, higher education has undergone significant changes due to the use of digital technologies and innovations. The use of innovative platforms, hybrid models and online services cannot overcome the requirements of ...

In recent times, researchers across various fields have become interested in the topic of fractional calculus based on integrals and derivatives of fractional order. This area has numerous and widespread applications in ...

Subjects / keywords: axiomatic theories in physics and in mathematics, mathematical analysis, classical and fuzzy set theories, differential equations and dynamical systems, mathematical problems of artificial intelligence, interdisciplinary...

Amid the convergence of technological, macroevolutionary, and demographic singularities, conventional approaches to analyzing and forecasting economic growth are increasingly losing relevance and predictive power. The su...

Reinforcement learning (RL) is a widely used learning paradigm that has shown significant successes in solving many hard AI problems including mastering real-time strategy games, autonomous car driving, and LLM model ali...

Subjects / keywords: Computer science; Travelling salesman problem; Computation; Nonlinear system; Optimization problem; Artificial neural network; Mathematical optimization; Combinatorial optimization; Analog computer; Artificial intelligen...

Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is increasingly important to be...

A Mathematical Introduction to Robotic Manipulation presents a mathematical formulation of the kinematics, dynamics, and control of robot manipulators. It uses an elegant set of mathematical tools that emphasizes the geo...

How do people know as much as they do with as little information as they get? The problem takes many forms; learning vocabulary from text is an especially dramatic and convenient case for research. A new general theory o...

We need scarcely add that the contemplation in natural science of a wider domain than the actual leads to a far better understanding of the actual.' (p. 267,The, Nature of the Physical World.)x PREFACE evolutionary theor...

A major assumption in many machine learning and data mining algorithms is that the training and future data must be in the same feature space and have the same distribution. However, in many real-world applications, this...

1. Introduction. Control System Design Steps. Adaptive Control. A Brief History. 2. Models for Dynamic Systems. Introduction. State-Space Models. Input/Output Models. Plant Parametric Models. Problems. 3. Stability. Intr...

Automated structure validation was introduced in chemical crystallography about 12 years ago as a tool to assist practitioners with the exponential growth in crystal structure analyses. Validation has since evolved into ...

Many optimization problems in various fields have been solved using diverse optimization al gorithms. Traditional optimization techniques such as linear programming (LP), non-linear programming (NLP), and dynamic program...

Swarm intelligence is a relatively new approach to problem solving that takes inspiration from the social behaviors of insects and of other animals. In particular, ants have inspired a number of methods and techniques am...

Evolutionary algorithms (EAs) are often well-suited for optimization problems involving several, often conflicting objectives. Since 1985, various evolutionary approaches to multiobjective optimization have been develope...

We shall present here the motivation and a general description of a method dealing with a class of problems in mathematical physics. The method is, essentially, a statistical approach to the study of differential equatio...

During the last decade, the data sizes have grown faster than the speed of processors. In this context, the capabilities of statistical machine learning methods is limited by the computing time rather than the sample siz...

A framework is developed to explore the connection between effective optimization algorithms and the problems they are solving. A number of "no free lunch" (NFL) theorems are presented which establish that for any algori...

Image-to-image translation is a class of vision and graphics problems where the goal is to learn the mapping between an input image and an output image using a training set of aligned image pairs. However, for many tasks...

From the Publisher: This book brings together - in an informal and tutorial fashion - the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic al...

Kernel methods provide a powerful and unified framework for pattern discovery, motivating algorithms that can act on general types of data (e.g. strings, vectors or text) and look for general types of relations (e.g. ran...

From the Publisher: This comprehensive treatment of the analysis and design of continuous-time control systems provides a gradual development of control theory—and shows how to solve all computational problems with MATL...