This volume features contributions to agent-based computational modeling from the social sciences and computer sciences. It presents applications of methodologies and tools, focusing on the uses, requirements, and constraints of agent-based models used by social scientists. Topics include agent-based macroeconomics, the emergence of norms and conventions, the dynamics of social and economic networks, and behavioral models in financial markets.
Macroeconomic Issues.- Beyond the Static Money Multiplier: In Search of a Dynamic Theory of Money.- Macroeconomic Effects of the Interest Rate Level: Growth and Fluctuations in an Economy with Bank Capital Adequacy Standards.- Monetary Policy Experiments in an Artificial Multi-Market Economy with Reservation Wages.- Market Mechanisms and Agents Behavior.- Testing Double Auction as a Component Within a Generic Market Model Architecture.- A Conceptual Framework for the Evaluation of Agent-Based Trading and Technical Analysis.- Which Market Protocols Facilitate Fair Trading?.- Market Dynamics and Efficiency.- An Artificial Economics View of the Walrasian and Marshallian Stability.- The Performance of Option―Trading Software Agents: Initial Results.- Studies on the Impact of the Option Market on the Underlying Stock Market.- On Rational Noise Trading and Market Impact.- Analysis of Economic and Social Networks.- A Note on Symmetry in Job Contact Networks.- Innovation and Knowledge Spillovers in a Networked Industry.- Heterogeneous Agents with Local Social Influence Networks: Path Dependence and Plurality of Equilibria in the ACE Noiseless Case.- Economy-Driven Shaping of Social Networks and Emerging Class Behaviors.- Group Effect, Productivity and Segregation Optimality.- The Grass is Always Greener on the Other Side of the Fence: The Effect of Misperceived Signalling in a Network Formation Process.- Methodological Issues and Applications.- Market Selection of Competent Venture Capitalists.- A Binary Particle Swarm Optimization Algorithm for a Double Auction Market.- Better-Reply Strategies with Bounded Recall.