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Provides a thorough survey of current research work in max-plus linear systems. This book summarizes the main mathematical concepts required for a theory of max-plus linear systems, including idempotent semirings, residuation theory, fixed point equations in the max-plus algebra, formal power series, and timed-event graphs.

Provides a comprehensive overview of game theory covering the foundations of the theory of non-cooperative and cooperative games, both static and dynamic. The book also highlights new trends in cooperative differential games, learning, approachability (games with vector payoffs) and mean-field games (large number of homogeneous players).

A reset controller is a linear controller whose output is reset to zero whenever its input and output satisfy an appropriate algebraic relationship. This monograph gives an in-depth assessment of the state-of-the-art and provides the reader with a starting point for further research into the increasingly important topic of Reset Control Systems.

Provides a comprehensive overview of the most common approaches used to design distributed optimization algorithms, together with the theoretical analysis of the main schemes in their basic version. The book identifies and formalizes classes of problem set-ups that arise in motivating application scenarios.

Provides a comprehensive survey of intelligent tools for analysis and design that take fundamental steps towards achieving resilient operation in Cyber-Physical Systems. The authors investigate the challenges of achieving reliable control and estimation over networks, particularly in the face of uncertainty and resource constraints.

Formalizes the ecologist's regime shift concept that allows the identification of two distinct regime shift mechanisms, shock-induced and bifurcation-induced regime shift, before defining ecological resilience as a regime transition system.

Provides the reader with an accessible primer on a new direction in control theory still in its infancy, namely Learning-Based Control Theory, that is closely tied to the literature of safe Reinforcement Learning and Adaptive Dynamic Programming.

Describes the use of principles of reinforcement learning (RL) to design feedback policies for continuous-time dynamical systems that combine features of adaptive control and optimal control. The authors give an insightful introduction to reinforcement learning techniques that can address various control problems.

Describes in detail the research on fault diagnosis, opacity analysis and enhancement, and cyber security analysis and enforcement, within suitable discrete event system modelling frameworks. In each case, the authors describe basic problem statements and key concepts, and then point out the key challenges in each research area.

This book provides an accessible overview of the complexities of generalized coordination for students, researchers and practitioners alike. Covering both theory and practical issues, the authors provide examples throughout to clearly illustrate the concepts being discussed.

Presents some existing and new results on analysis and design of finite-time and fixed-time converging systems. Two main groups of approaches for analysis/synthesis of this kind of convergence, Lyapunov functions and the theory of homogeneous systems, are considered.