This book pursues a nonlinear approach in considering both chaotic dynamical models and agent-based simulation models of economics, as well as their dynamical behaviors. Three key concepts arising in this context are “nonlinearity,” “bounded rationality” and “heterogeneity,” which...

The field of artificial economics (AE) embraces a broad range of methodologies relying on computer simulations in order to model and study the complexity of economic and social phenomena. The overarching principle of AE is the analysis of aggregate properties of artificial economies populated by...

Introduction -- Technological Progress: Logistic Growth or Singularity -- Artificial Intelligence -- Artificial Happiness -- Issues in Artificial Intelligence -- Artificial Intelligence in Economics: ACE -- Economics of Artificial Intelligence -- State of the Art, Challenges for AGI

Markets and Trading -- Agent’s Minimal Intelligence Calibration for Realistic Market Dynamics -- Trading on Marginal Information -- Stylized Facts Study through a Multi-Agent Based Simulation of an Artificial Stock Market -- Auctions -- A Variable Bid Increment Algorithm for Reverse English...

The results of an experiment extending Ellsberg's setup demonstrate that attitudes towards ambiguity and compound uncertainty are closely related. However, this association is much stronger when the second layer of uncertainty is subjective than when it is objective. Provided that the compound...

The catastrophic events are characterized by "low frequency and high severity". Nevertheless, during the last decades, both the frequency and the magnitude of these events have been significantly rising worldwide. In 2021, the European Commission adopted a new Strategy on Adaptation to Climate...

Anscombe and Aumann (1963) offer a definition of subjective probability in terms of comparisons with objective probabilities. That definition - which has provided the basis for much of the succeeding work on subjective probability - presumes that the subjective probability of an event is...

Managing Uncertainty, Mitigating Risk proposes that financial risk management broaden its approach, maintaining quantification where possible, but incorporating uncertainty. The author shows that by using broad quantification techniques, and using reason as the guiding principle, practitioners...