Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective.
Most subfields of computer science have an interface layer via which applications communicate with the infrastructure, and this is key to their success (e.
Semi-supervised learning is a learning paradigm concerned with the study of how computers and natural systems such as humans learn in the presence of both labeled and unlabeled data.
Robotics technology has recently advanced to the point of being widely accessible for relatively low-budget research, as well as for graduate, undergraduate, and even secondary and primary school education.
Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning.
This book starts with an introduction to the basic concepts of multistability, then illustrates how multistability arises in different systems and explains the main mechanisms of multistability emergence.
This contributed volume investigates several mathematical techniques for the modeling and simulation of viral pandemics, with a special focus on COVID-19.
This contributed volume convenes a rich selection of works with a focus on innovative mathematical methods with applications in real-world, industrial problems.
This book includes contributions about mathematics, physics, philosophy of science, economics and finance and resulted from the Summer School "e;Complexity and Emergence: Ideas, Methods, with a Special Attention to Economics and Finance"e; held in Lake Como School of Advanced Studies, on 22-27 July 2018.
This book contains the papers presented at the XXX International Congress INGEGRAF, "e;Digital Engineering, its application in Research, Development and Innovation"e;, held on 24-25 June 2021 in Valencia, Spain.
This edited volume collects six surveys that present state-of-the-art results on modeling, qualitative analysis, and simulation of active matter, focusing on specific applications in the natural sciences.
This book discusses the P-graph framework for developing and understanding effective design tools for process systems engineering, and addresses the current state of its theory and applications.
This book introduces readers to benchmarking techniques in the stochastic environment, primarily stochastic data envelopment analysis (DEA), and provides stochastic models in DEA for the possibility of variations in inputs and outputs.
The Mathematics of Errors presents an original, rigorous and systematic approach to the calculus of errors, targeted at both the engineer and the mathematician.
MATLAB and Simulink Crash Course for Engineers is a reader-friendly introductory guide to the features, functions, and applications of MATLAB and Simulink.
The investigation of the role of mechanical and mechano-chemical interactions in cellular processes and tissue development is a rapidly growing research field in the life sciences and in biomedical engineering.
This book directs the engineering manager or the undergraduate student preparing to become an engineering manager, who is or will become actively engaged in the management of economic-risk trade-off decisions for engineering investments within an organizational system.
The 5th edition of this classic textbook covers the central concepts of practical optimization techniques, with an emphasis on methods that are both state-of-the-art and popular.
Curated by the Fields Institute for Research in Mathematical Sciences from their COVID-19 Math Modelling Seminars, this first in a series of volumes on the mathematics of public health allows readers to access the dominant ideas and techniques being used in this area, while indicating problems for further research.
This innovative textbook brings together modern concepts in mathematical epidemiology, computational modeling, physics-based simulation, data science, and machine learning to understand one of the most significant problems of our current time, the outbreak dynamics and outbreak control of COVID-19.
Fuzzy cognitive maps (FCMs) have gained popularity in the scientific community due to their capabilities in modeling and decision making for complex problems.
This monograph demonstrates a new approach to the classical mode decomposition problem through nonlinear regression models, which achieve near-machine precision in the recovery of the modes.
This book offers a broad overview of the field of cognitive engineering and neuroergonomics, covering emerging practices and future trends toward the harmonious integration of human operators and computational systems.
This volume is part of collection of contributions devoted to analytical and experimental techniques of dynamical systems, presented at the 15th International Conference "e;Dynamical Systems: Theory and Applications"e;, held in Lodz, Poland on December 2-5, 2019.
