Adaptive processes and economic theory; Biological systems as paradigms for adaptation; Optimization and evolution in the theory of the firm; The market adaptation of the firm; Learning by firms about demand conditions; Further notes on the allocation of effort.

This first volume in a three-volume exposition of Shubik's vision of "mathematical institutional economics" explores a one-period approach to economic exchange with money, debt, and bankruptcy. This is the first volume in a three-volume exposition of Martin Shubik's vision of "mathematical institutional economics"--a term he coined in 1959 to describe the theoretical underpinnings needed for the construction of an economic dynamics. The goal is to develop a process-oriented theory of money and financial institutions that reconciles micro- and macroeconomics, using as a prime tool the theory of games in strategic and extensive form. The approach involves a search for minimal financial institutions that appear as a logical, technological, and institutional necessity, as part of the "rules of the game." Money and financial institutions are assumed to be the basic elements of the network that transmits the sociopolitical imperatives to the economy. Volume 1 deals with a one-period approach to economic exchange with money, debt, and bankruptcy. Volume 2 explores the new economic features that arise when we consider multi-period finite and infinite horizon economies. Volume 3 will consider the specific role of financial institutions and government, and formulate the economic financial control problem linking micro- and macroeconomics.

A new, evolutionary explanation of markets and investor behavior Half of all Americans have money in the stock market, yet economists can’t agree on whether investors and markets are rational and efficient, as modern financial theory assumes, or irrational and inefficient, as behavioral economists believe. The debate is one of the biggest in economics, and the value or futility of investment management and financial regulation hangs on the answer. In this groundbreaking book, Andrew Lo transforms the debate with a powerful new framework in which rationality and irrationality coexist—the Adaptive Markets Hypothesis. Drawing on psychology, evolutionary biology, neuroscience, artificial intelligence, and other fields, Adaptive Markets shows that the theory of market efficiency is incomplete. When markets are unstable, investors react instinctively, creating inefficiencies for others to exploit. Lo’s new paradigm explains how financial evolution shapes behavior and markets at the speed of thought—a fact revealed by swings between stability and crisis, profit and loss, and innovation and regulation. An ambitious new answer to fundamental questions about economics and investing, Adaptive Markets is essential reading for anyone who wants to understand how markets really work.

Adaptive Economic Models provides information pertinent to the adaptive processes in economics. This book discusses the developments on research in the field of adaptive economics. Organized into 23 chapters, this book begins with an overview of the study of economic processes using concepts of adaptation. This text then explains how concepts arising from biology can be formulated in such a way that they can be a source of insight into man's social systems. Other chapters present a general view of the adaptation of the firm to its environment and discuss how a firm with a definite commodity in mind can decide whether to enter a given established market. This book discusses as well the simple duopoly problem in which firms are in error in the sense that they specify an incomplete model and add a random error term. The final chapter deals with the set of models and problems for the development of a theory of money and financial institutions. This book is a valuable resource for economic theorists and economists.

Learning Classifier Systems (LCS) are a machine learning paradigm introduced by John Holland in 1976. They are rule-based systems in which learning is viewed as a process of ongoing adaptation to a partially unknown environment through genetic algorithms and temporal difference learning. This book provides a unique survey of the current state of the art of LCS and highlights some of the most promising research directions. The first part presents various views of leading people on what learning classifier systems are. The second part is devoted to advanced topics of current interest, including alternative representations, methods for evaluating rule utility, and extensions to existing classifier system models. The final part is dedicated to promising applications in areas like data mining, medical data analysis, economic trading agents, aircraft maneuvering, and autonomous robotics. An appendix comprising 467 entries provides a comprehensive LCS bibliography.

Model Building is the most fruitful area of economics, designed to solve real-world problems using all available methods such as mathematical, computational and analytical, without distinction. Wherever necessary, we should not be reluctant to develop new techniques, whether mathematical or computational. That is the philosophy of this volume. The volume is divided into three distinct parts: Methods, Theory and Applications. The Methods section is in turn subdivided into Mathematical Programming and Econometrics and Adaptive Control System, which are widely used in econometric analysis. The impacts of fiscal policy in a regime with independent monetary authority and dynamic models of environmental taxation are considered. In the section on "Modelling Business Organization," a model of a Japanese organization is presented. Furthermore, a model suitable for an efficient budget management of a health service unit by applying goal programming method is analyzed, taking into account various socio-economic factors. This is followed by a section on "Modelling National Economies," in which macroeconometric models for the EU member countries are analyzed, to find instruments that stabilize inflation with coordinated action.

This book addresses central issues in evolutionary and Schumpeterian accounts of industrial competition, learning, and innovation. It contains a collection of twelve papers which are oriented toward exploring methodological issues in evolutionary and related scholarship. Reflecting the diversity of work in evolutionary scholarship, a range of methodologies are employed in the papers, including simulation, experiments, and econometric analysis. Some of the papers use well established models to takle new questions and problems. Others introduce entirely new approaches, which the authors indicate are still in a state of infancy and await further development. The collection attempts to raise even more interest in evolutionary economics, to provide some suggestions for future research directions, and to initiate a lively discussion of the issues raised.