In recent years, agent-based simulation has become a widely accepted tool when dealing with complexity in economics and other social sciences. The contributions presented in this book apply agent-based methods to derive results from complex models related to market mechanisms, evolution, decision making, and information economics. In addition, the applicability of agent-based methods to complex problems in economics is discussed from a methodological perspective. The papers presented in this collection combine approaches from economics, finance, computer science, natural sciences, philosophy, and cognitive sciences.

A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.

A collection of previous published papers by the author on the subject of complexity economics, appearing from the 1980s to the present.

This volume explores the field of artificial intelligence and features in-depth coverage of important theoretical areas including computational organization, computational economics, computational approaches in social science, and game theory. The conception of the multi-agent system is particularly attractive, as it promises autonomy based on the conceptual speciality of a rational agent as well as collective behaviour through interactions.

"This book describes a holistic approach to monitoring, evaluating, and applying appropriate marketing strategies, and understanding the competition and its future implication on the business of a company"--Provided by publisher.

This book interprets insights from the complexity sciences to explore seven types of complexity better to understand the predictable unpredictability of social life. Drawing on the natural and social sciences, it describes how complexity models are helpful but insufficient for our understanding of complex reality. Taking an interdisciplinary approach, the book develops a complex theory of action more consistent with our experience that our plans inevitably lead to unexpected outcomes, explains why we are both individuals and thoroughly social, and gives an account of why, no matter how clear our message, we may still be misunderstood. The book investigates what forms of knowledge are most helpful for thinking about complex experience, reflects on the way we exercise authority (leadership) and thinks through the ethical implications of trying to co-operate in a complex world. Taking complexity seriously poses a radical challenge to more orthodox theories of managing and leading, based as they are on assumptions of predictability, control and universality. The author argues that management is an improvisational practice which takes place in groups in a particular context at a particular time. Managers can influence but never control an uncontrollable world. To become more skilful in complex group dynamics involves taking into account multiple points of view and acknowledging not knowing, ambivalence and doubt. This book will be of interest to researchers, professionals, academics and students in the fields of business and management, especially those interested in how taking complexity seriously can influence the functioning of businesses and organizations and how they manage and lead.

This book constitutes the thoroughly refereed joint post-proceedings of five international workshops organized by the Japanese Society of Artificial Intelligence, JSAI in 2001.The 75 revised papers presented were carefully reviewed and selected for inclusion in the volume. In accordance with the five workshops documented, the book offers topical sections on social intelligence design, agent-based approaches in economic and complex social systems, rough set theory and granular computing, chance discovery, and challenges in knowledge discovery and data mining.