What is the way out of this dilemma? Some relevant papers from the last ESCIM-2020 are included in this volume. However, it is far from being a ready to use and complete collection of approaches, and is rather a continuously developing field without clear borders..

ROS is currently considered as the primary development framework for robotics applications. This book is the sixth volume of the successful book series on Robot Operating System: The Complete Reference.

This book is the sixth volume of the successful book series on Robot Operating System: The Complete Reference.0 is become increasingly mature to be integrated into the industry.

The main part of the book is devoted to a very challenging problem of stock market recommendations. The book proposes techniques, with an emphasis on the financial sector, which will make recommendation systems both accurate and explainable. First, the main idea of the explainable recommenders is outlined within the background of neuro-fuzzy systems.In turn, various novel recommenders are proposed, each characterized by achieving high accuracy with a reasonable number of interpretable fuzzy rules.

Explainable Artificial Intelligence Based on Neuro-Fuzzy Modeling with Applications in Finance. An original concept of the explainable recommender, based on patterns from previous transactions, is developed; it recommends stocks that fit the strategy of investors, and its recommendations are explainable for investment advisers. First, the main idea of the explainable recommenders is outlined within the background of neuro-fuzzy systems. Therefore, the development of artificial intelligence cannot ignore the need for interpretable, transparent, and explainable models.

Part III provides three chapters on ROS navigation. The first chapter deals with the use of deep learning for ROS navigation. I believe that this book is a valuable companion for ROS users and developers to learn more ROS capabilities and features.

The essays reflect the extent, diversity, and richness of several research areas, both normative and descriptive, and are an invaluable resource for graduate-level and PhD students, academics, researchers, policymakers and other professionals, especially in the social and cognitive sciences.

Decision Economics: Minds, Machines, and their Society It is the fifth volume to emerge from that international project, held under the aegis of the United Nations Academic Impact in 2020.

The book proposes techniques, with an emphasis on the financial sector, which will make recommendation systems both accurate and explainable. An original concept of the explainable recommender, based on patterns from previous transactions, is developed; it recommends stocks that fit the strategy of investors, and its recommendations are explainable for investment advisers. First, the main idea of the explainable recommenders is outlined within the background of neuro-fuzzy systems.

. The book is intended for readers from the ranks of academic staff, students of universities of economics, but also the scientists and practitioners dealing with the time series prediction.their specific use in practice.e.

Furthermore, a comprehensive comparative analysis of the individual methods is provided.. Using Artificial Neural Networks for Timeseries Smoothing and Forecasting Both statistical and econometric methods, and especially artificial intelligence methods, are used in the case studies. The aim of this publication is to identify and apply suitable methods for analysing and predicting the time series of gold prices, together with acquainting the reader with the history and characteristics of the methods and with the time series issues in general.

The publication presents both traditional and innovative methods on the theoretical level, always accompanied by a case study, i. The book is intended for readers from the ranks of academic staff, students of universities of economics, but also the scientists and practitioners dealing with the time series prediction.. Using Artificial Neural Networks for Timeseries Smoothing and Forecasting Both statistical and econometric methods, and especially artificial intelligence methods, are used in the case studies.

Deep Learning in Computational Mechanics To achieve this goal, mostly one-dimensional examples are investigated, such as approximating functions by neural networks or the simulation of the temperature’s evolution in a one-dimensional bar.This book provides a first course on deep learning in computational mechanics. The idea of the book is to provide the basic concepts in a mathematically sound manner and yet to stay as simple as possible.

This book provides a first course on deep learning in computational mechanics. The idea of the book is to provide the basic concepts in a mathematically sound manner and yet to stay as simple as possible. It then provides an overview of current topics in physics and engineering, setting the stage for the book’s main topics: physics-informed neural networks and the deep energy method.

. The book starts with a short introduction to machine learning’s fundamental concepts before neural networks are explained thoroughly.

This book lists current and potential biomedical uses of computational intelligence methods.

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Soft Computing: Biomedical and Related Applications The book describes several such promising new methods that have been tested on problems from agriculture, computer networks, economics and business, pavement engineering, politics, quantum computing, robotics, etc.. These methods are used in diagnostics and treatment of such diseases as cancer, cardiac diseases, pneumonia, stroke, and COVID-19.This book lists current and potential biomedical uses of computational intelligence methods.

This collection of contributions (17 chapters and 2 short papers) provides researchers and practitioners the latest advances in educational robotics in a broader sense focusing on science, technology, engineering, arts, and mathematics (STEAM) education. Education in & with Robotics to Foster 21st-Century Skills. The contributions cover a variety of topics useful for teacher education and for designing learning by making activities for children and youth, with an emphasis on modern low-cost technologies (including block-based programming environments, Do-It-Yourself electronics, 3D printed artifacts, the use of intelligent distributed systems, the IoT technology, and gamification) in formal and informal education settings.

The contributions cover a variety of topics useful for teacher education and for designing learning by making activities for children and youth, with an emphasis on modern low-cost technologies (including block-based programming environments, Do-It-Yourself electronics, 3D printed artifacts, the use of intelligent distributed systems, the IoT technology, and gamification) in formal and informal education settings. This book includes papers presented at the International Conference “Educational Robotics in the Maker Era – EDUROBOTICS 2020”, Online, February 2021.This collection of contributions (17 chapters and 2 short papers) provides researchers and practitioners the latest advances in educational robotics in a broader sense focusing on science, technology, engineering, arts, and mathematics (STEAM) education.

To be able to do that, we need to have a good understanding of what causes what in economics.

Prediction and causality in economics are the main topics of this book's chapters; they use both more traditional and more innovative techniques—including quantum ideas -- to make predictions about the world economy (international trade, exchange rates), about a country's economy (gross domestic product, stock index, inflation rate), and about individual enterprises, banks, and micro-finance institutions: their future performance (including the risk of bankruptcy), their stock prices, and their liquidity.Prediction and Causality in Econometrics and Related Topics Several papers study how COVID-19 has influenced the world economy..

. This book is dedicated to user experience design for automated driving to address humane aspects of automated driving, e. A variety of application scenarios and restrictions has been ambiguous.

, workload, safety, trust, ethics, and acceptance.

Prediction and Causality in Econometrics and Related Topics Several papers study how COVID-19 has influenced the world economy. This book helps practitioners and researchers to learn more about prediction and causality in economics -- and to further develop this important research direction.

Manned and unmanned ground, aerial and marine vehicles enable many promising and revolutionary civilian and military applications that will change our life in the near future.

The book is primarily meant for researchers from academia and industry, who are working on in the research areas such as engineering, control engineering, robotics, mechatronics, biomedical engineering, mechanical engineering and computer science. This book is used at the graduate or advanced undergraduate level and many others. Moreover, deep learning methods have been recently actively developed in other areas of machine learning, including reinforcement training and transfer/meta-learning, whereas standard, deep learning methods such as recent neural network (RNN) and coevolutionary neural networks (CNN).

This book is dedicated to user experience design for automated driving to address humane aspects of automated driving, e.

The book chapters discuss details of applications and future research areas. The book chapters are well written with a good exposition of the research problem, methodology, block diagrams and mathematical techniques.

Computer and Information Science 2021—Summer The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way.The conference organizers selected the best papers from those papers accepted for presentation at the conference.. This edited book presents scientific results of the 20th IEEE/ACIS International Summer Semi-Virtual Conference on Computer and Information Science (ICIS 2021) held on June 23–25, 2021 in Shanghai, China.