JASA is a high-performance auction simulator written in JAVA. It is designed for performing experiments in agent-based computational economics.
This package is currently at alpha. This code is not stable or fully tested. Please report any bugs, issues or suggestions to Steve Phelps.
This software is licensed under the GNU General Public License. Although it is not an official term of the licensing conditions, you are also expected to cite use of this software if you use it in your research.
The latest release of JASA can be downloaded from SourceForge.
- Java JVM 1.6.0 or later
- JASA is built on top of the JABM framework which must be installed before using JASA.
The distribution archive can be imported directly into the Eclipse
IDE by using the
File/Import
menu item. Create a launch
configuration
with the main class net.sourceforge.jabm.DesktopSimulationManager and
specify which configuration file you want to use by setting the system
property jabm.config using the JVM argument -D, for example
-Djabm.config=examples/chiarellaAndIori/main.xml
Additional contributors: Jinzhong Niu and Marek Marcinkiewicz.
This work has been supported by EPSRC grant GR/T10671/01 - "Market Based Control of Complex Computational Systems." and NSF grant number IIS-9820657 - "Tools and Techniques for Automated Mechanism Design". It was originally supported by the EU IST Programme through the SLIE project.
The system is based on the 4-heap algorithm, described in the paper
Wurman, P. R., Walsh, W. E., & Wellman, M. P. (1998). Flexible double auctions for electronic commerce: theory and implementation. International Journal of Decision Support Systems, 24, 17–27.
JASA makes use of the Mersenne Twister PRNG. Full details of the Mersenne Twister algorithm can be found in:
Makato Matsumoto and Takuji Nishimura, "Mersenne Twister: A 623-Dimensionally Equidistributed Uniform Pseudo-Random Number Generator", in ACM Transactions on modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3--30.
JASA includes implementations based on existing agent-based models described in the literature, including:
- Iori, G., & Chiarella, C. (2002). A Simulation Analysis of the Microstructure of Double Auction Markets. Quantitative Finance, 2, 346–353.
- Cliff, D., & Bruten, J. (1997). Minimal-Intelligence Agents for Bargaining Behaviors in Market-Based Environments.
- Nicolaisen, J., Petrov, V., & Tesfatsion, L. (2001). Market power and efficiency in a computational electricity market with discriminatory double-auction pricing. IEEE Transactions on Evolutionary Computation, 5(5), 504–523.
This product includes software developed by the Apache Software Foundation (http://www.apache.org).
(C) 2014 Steve Phelps