This book aims to answer two questions that are fundamental to the study of agent-based economic models: what is agent-based computational economics and why do we need agent-based economic modelling of economy? This book provides a review of the development of agent-based computational economics (ACE) from a perspective on how artificial economic agents are designed under the influences of complex sciences, experimental economics, artificial intelligence, evolutionary biology, psychology, anthropology and neuroscience. This book begins with a historical review of ACE by tracing its origins. From a modelling viewpoint, ACE brings truly decentralized procedures into market analysis, from a single market to the whole economy. This book also reviews how experimental economics and artificial intelligence have shaped the development of ACE. For the former, the book discusses how ACE models can be used to analyse the economic consequences of cognitive capacity, personality and cultural inheritance. For the latter, the book covers the various tools used to construct artificial adaptive agents, including reinforcement learning, fuzzy decision rules, neural networks, and evolutionary computation. This book will be of interest to graduate students researching computational economics, experimental economics, behavioural economics, and research methodology.

Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable solutions for many real-world problems, but the often informal way in which they are defined and applied has led to misconceptions, and even successful applications are sometimes the outcome of trial and error. Ideally, theoretical studies should explain when and why metaheuristics work, but the challenge is huge: mathematical analysis requires significant effort even for simple scenarios and real-life problems are usually quite complex. In this book the editors establish a bridge between theory and practice, presenting principled methods that incorporate problem knowledge in evolutionary algorithms and other metaheuristics. The book consists of 11 chapters dealing with the following topics: theoretical results that show what is not possible, an assessment of unsuccessful lines of empirical research; methods for rigorously defining the appropriate scope of problems while acknowledging the compromise between the class of problems to which a search algorithm is applied and its overall expected performance; the top-down principled design of search algorithms, in particular showing that it is possible to design algorithms that are provably good for some rigorously defined classes; and, finally, principled practice, that is reasoned and systematic approaches to setting up experiments, metaheuristic adaptation to specific problems, and setting parameters. With contributions by some of the leading researchers in this domain, this book will be of significant value to scientists, practitioners, and graduate students in the areas of evolutionary computing, metaheuristics, and computational intelligence.

Attempts to construct an integrated conceptual framework for the application-neutral and problem-neutral representation of sources of law using Semantic Web technology and concepts and some technically straightforward extensions to Semantic Web technology based on established practices found in fielded applications.

This book analyses decision-making in dynamic economic environments. By applying a wide range of methodological approaches, combining both analytical and computational methods, the contributors examine various aspects of optimal firm behaviour and relevant policy areas. Topics covered include optimal control, dynamic games, economic decision-making, and applications in finance and economics, as well as policy implications in areas such as pollution regulation. This book is dedicated to Christophe Deissenberg, a well-known and distinguished scholar of economic dynamics and computational economics. It appeals to academics in the areas of optimal control, dynamic games and computational economics as well as to decision-makers working in policy domains such as environmental policy.

The fully updated second edition of this innovative textbook provides a system analysis approach to sustainability for advanced undergraduate and graduate students. To an extent unparalleled in other textbooks, the latest scientific data and insights are integrated into a broad and deep transdisciplinary framework. Readers are encouraged to explore and engage with sustainability issues through the lenses of a cultural and methodological pluralism which promotes dialogue and alliances in the search for a (more) sustainable future. Ideal for students and their teachers in sustainable development, environmental science and policy, ecology, conservation, natural resources and geopolitics, the book will also appeal to interested citizens, activists, and policymakers, exposing them to the variety of perspectives on sustainability issues. Review questions and exercises provide the opportunity for consolidation and reflection. Online resources include appendices with more advanced mathematical material, model answers, and a wealth of recommended additional sources.

The Oxford Handbook of Computational Economics and Finance provides a survey of both the foundations of and recent advances in the frontiers of analysis and action. It is both historically and interdisciplinarily rich and also tightly connected to the rise of digital society. It begins with the conventional view of computational economics, including recent algorithmic development in computing rational expectations, volatility, and general equilibrium. It then moves from traditional computing in economics and finance to recent developments in natural computing, including applications of nature-inspired intelligence, genetic programming, swarm intelligence, and fuzzy logic. Also examined are recent developments of network and agent-based computing in economics. How these approaches are applied is examined in chapters on such subjects as trading robots and automated markets. The last part deals with the epistemology of simulation in its trinity form with the integration of simulation, computation, and dynamics. Distinctive is the focus on natural computationalism and the examination of the implications of intelligent machines for the future of computational economics and finance. Not merely individual robots, but whole integrated systems are extending their "immigration" to the world of Homo sapiens, or symbiogenesis.

Innovation is increasingly recognized as a vitally important social and economic phenomenon worthy of serious research study. The book, written by leading contributors to the field, examines the state of the art and achievements in the relatively new field of Innovation Studies, as well as what future challenges lie ahead.