Agent-Directed Simulation
Under Construction Last Updated: 2004-06-27 Site Maintained by: Levent Yilmaz Auburn Modeling and Simulation Laboratory of the M&SNet Department of Computer Science and Engineering College of Engineering Auburn University Email:  yilmaz@eng.auburn.edu

Introductory Material and Resources on Agent Systems and their Simulation:

Joshua Epstein, Agent-Based Computational Models and Generative Social Science, Complexity, Vol. 4/No. 5, May/June 1999, 41-60.

A.M.Uhrmacher, B.Schattenberg, Agents in Discrete Event Simulation. In: Proc. of the ESS'98, October 26-28, Nottingham, SCS Publications, Ghent, 129-136, 1998.

Marcenac P., Multi-Agent Simulation in Social Science Applications, Complexity International, vol. 3 1996.

Sallach D. Social theory and agent architectures: prospective issues in rapid-discovery social science , Social Science Computer Review, Volume 21 ,  Issue 2  (June 2003)

• D. Hales, B. Edmonds, E. Norling, J. Rouchier, editors:

  Multi-Agent-Based Simulation III.

  Springer-Verlag Lecture Notes in AI Volume 2927, December 2003.
  Click here to get the book contents, if you have access to SpringerLink

• J.S. Sichman, F. Bousquet, P. Davidsson, editors:

  Multi-Agent-Based Simulation II.

  Springer-Verlag Lecture Notes in AI Volume 2581, January 2003.
  Click here to get the book contents, if you have access to SpringerLink.

• S. Moss, P. Davidsson, editors:

  Multi-Agent-Based Simulation.

  Springer-Verlag Lecture Notes in AI Volume 1979, November 2000.
  Click here to get the book contents, if you have access to SpringerLink.

ACE. Agent-based computational economics (ACE) is the computational study of economies modeled as evolving systems of autonomous interacting agents.

CASOS. Computational Analysis of Social and Organizational Systems. "Groups, organizations, and societies are inherently computational and computational multi-agent systems are inherently organizational. Thus, within CASOS we attempt to understand and formally model two distinct but complimentary types of phenomena. The first is the natural or human group, organizational or society, which continually acquires, manipulates, and produces information (and possibly other material goods) through the joint, and interlocked activities of people and automated information technologies. The second is the artificial computational systems which is generally comprised of multiple distributed agents who can mutually influence, constrain and suppurt each other as they try to manage and manipulate the knowledge, communication and interaction networks in which they are embedded. Computational analysis is used to develop a better understanding of the fundamental principles of organizing, coordinating, and managing multiple information processing agents (whether they are human, WebBot, or robots) and the fundamental dynamic nature of groups, organizations and societies." - from their Mission Statement

The Smartest Agents Will Learn to Be Team Players. By Christopher Locke. Red Herring (January 9, 2002).

MultiAgent Systems. By Katia Sycara (1998). AI Magazine 19(2). Discusses the need for multiple agent systems communicating peer-to-peer. (See quote above.)

Agent technology: removing the 'artificial' from AI. By Fran Howarth. IT-Director.com (March 18, 2004).

Intelligent Agents and Multi-Agents. From ASAP, the Automated Scheduling, Optimization and Planning group, School of Computer Science and Information Technology, University of Nottingham.

Distributed Agents from IEEE Distributed Systems Online

Multiagent Systems: An Emerging Subdiscipline of AI. Victor R. Lesser (1995). ACM Computing Surveys, 27 (3): 340 -342.

Standardization of Agent System Frameworks. By Roberto A. Flores-Mendez. ACM Crossroads, 5(4).

Journal of Artificial Societies and Social Simulation, "an inter-disciplinary journal for the exploration and understanding of social processes by means of computer simulation."

Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence. Reviewed by Julie A. Adams. AI Magazine 22(2): 105-108 (Summer 2001).

AI think, therefore I am. Virtual agents feature - Computerised characters that look, sound, move and seemingly think like real people are emerging from the realms of science fiction into everyday life. Superguide by David Braue. apcmag.com (December 16, 2003). "

Agents of creation - Artificial “agents” can model complex systems. The Economist (October 9, 2003). "In this context, an agent is a program that acts in a self-interested manner in its dealings with numerous other agents inside a computer. This arrangement can mimic almost any interactive system: a stockmarket; a habitat; even a business supply-chain."

Collaborative Systems: 1994 AAAI Presidential Address. By Barbara Grosz. 1996. AI Magazine 17(2), 67-85.

Tutorial on Intelligent Agent Systems. By Vasant Honavar, Department of Computer Science, Iowa State University.

Game Theory. Daphne Koller's article for the MIT Encyclopedia of Cognitive Science. "Game theory is a mathematical framework designed for analyzing the interaction between several agents whose decisions affect each other. In a game-theoretic analysis, an interactive situation is described as a game: an abstract description of the players (agents), the courses of actions available to them, and their preferences over the possible outcomes. ... Unlike decision making for a single agent, in the multiagent case this assumption is not enough to define an 'optimal decision,' because the agent cannot unilaterally control the outcome."

• Also see:
  • What is game theory and what are some of its applications? Explained by Saul I. Gass. Scientific American - Ask the Experts (June 2, 2003).
  • Game Theory .net where you'll find lecture notes, news, games, dictionary, interactive materials, links to journals, and much more.

On the Backs of Ants - New networks mimic the behavior of insects and bacteria. By Kimberly Patch. Technology Review (March 19, 2003).

Multiagent Systems: A Survey from a Machine Learning Perspective. By Peter Stone and Manuela Veloso, Computer Science Department, Carnegie Mellon University. This survey of MAS is intended to serve as an introduction to the field and as an organizational framework.

Control of Agent Based Systems. Defense Advanced Research Projects Agency (DARPA), U.S. Department of Defense. Overviews and detailed descriptions of military research and simulation projects involving agents.

Distributed Artificial Intelligence links from the Department of Sociology, University of Surrey.

Learning in Multi-Agent Systems: Webliography. By M. V. Nagendra Prasad (University of Massachusetts, Amherst) and Thomas Haynes (University of Tulsa), Links to research sites, projects, conferences, journals and more.

Agent Systems. "This site contains pointers to information about multiagent systems, including both research and industrial references. The front page also has breaking news of some relevance." Maintained by José M Vidal.

Multi-Agent Systems at The Intelligent Software Agents Group, Robotics Institute, Carnegie Mellon University. Be sure to scroll down their page to their collection of "Applications of Multi-Agent Research."

The Agent Systems Laboratory at the Department of Computer Science at the University of Massachusetts at Amherst.

Open Agent Architecture - A framework for integrating a community of heterogeneous software agents in a distributed environment.

The Research Center for Team-Based Agents School of Information Sciences and Technology, The Pennsylvania State University aims to develop agents with 'team intelligence', which enables them to support and enhance collaborative activities of teams, which may include both human users and software agents.