Handbook of Computational Economics: Agent-Based Computational EconomicsLeigh Tesfatsion, Kenneth L. Judd The explosive growth in computational power over the past several decades offers new tools and opportunities for economists. This handbook volume surveys recent research on Agent-based Computational Economics (ACE), the computational study of economic processes modeled as dynamic systems of interacting agents. Empirical referents for "agents" in ACE models can range from individuals or social groups with learning capabilities to physical world features with no cognitive function. Topics covered include: learning; empirical validation; network economics; social dynamics; financial markets; innovation and technological change; organizations; market design; automated markets and trading agents; political economy; social-ecological systems; computational laboratory development; and general methodological issues. *Every volume contains contributions from leading researchers *Each Handbook presents an accurate, self-contained survey of a particular topic *The series provides comprehensive and accessible surveys |
Contents
Perspectives on the ACE Methodology | 1549 |
Guideline for Newcomers to AgentBased Modeling | 1645 |
Author Index | 1 |
| 27 | |
Handbooks in Economics | 39 |
Forthcoming Titles | 41 |
Other editions - View all
Handbook of Computational Economics, Volume 2 Hans M. Amman,Leigh Tesfatsion,Kenneth L. Judd,David A. Kendrick,John Rust No preview available - 2006 |
Common terms and phrases
ACE models adaptive agent-based computational agent-based computational economics agent-based models agents allocation analysis approach artificial asset pricing Axelrod bounded rationality buyers Cambridge chartists choice common-pool resources comp lab competitive complex Computational Economics consumers convergence cooperation decision developed discussed distribution double auction Duffy economists empirical endogenous environment equilibrium evolution evolutionary evolutionary algorithms evolve example exchange rate expectations experimental experiments fictitious play financial markets forecasting function fundamental fundamentalists genetic algorithm handbook hash firm heterogeneous human subject individual innovation interactions Journal of Economic landscape learning models learning processes market design mechanisms methods Nash equilibrium nodes nomic optimal organization organizational outcomes parameter payoff period players political population predictions problem profit random rational rational expectations reinforcement learning replicator dynamics rules sellers simple simulation small-world small-world networks social spatial stochastic strategies structure Tesfatsion theoretical theory tion types utility