An agent-based approach equipped with game theory: Strategic collaboration among learning agents during a dynamic market change in the California electricity crisis
An agent-based approach is a numerical (computer-intensive) method to explore the complex characteristics and dynamics of microeconomics. Using the agent-based approach, this study investigates the learning speed of traders and their strategic collaboration in a dynamic market change of electricity. An example of such a market change can be found in the California electricity crisis (2000-2001). This study incorporates the concept of partial reinforcement learning into trading agents and finds that they have two learning components: learning from a dynamic market change and learning from collaboration with other traders. The learning speed of traders becomes slow when a large fluctuation occurs in the power exchange market. The learning speed depends upon the type of traders, their learning capabilities and the fluctuation of market fundamentals. The degree of collaboration among traders gradually reduces during the electricity crisis. The strategic collaboration among traders is examined by a large simulator equipped with multiple learning capabilities.
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- Yoella Bereby-Meyer & Alvin E. Roth, 2006.
"The Speed of Learning in Noisy Games: Partial Reinforcement and the Sustainability of Cooperation,"
American Economic Review,
American Economic Association, vol. 96(4), pages 1029-1042, September.
- Roth, Alvin & Bereby-Meyer, Yoella, 2006. "The Speed of Learning in Noisy Games: Partial Reinforcement and the Sustainability of Cooperation," Scholarly Articles 2580381, Harvard University Department of Economics.
- Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
- Knittel, Christopher R. & Roberts, Michael R., 2005. "An empirical examination of restructured electricity prices," Energy Economics, Elsevier, vol. 27(5), pages 791-817, September.
- Makowski, Marek & Nakamori, Yoshiteru & Sebastian, Hans-Jurgen, 2005. "Advances in complex systems modeling," European Journal of Operational Research, Elsevier, vol. 166(3), pages 593-596, November.
- Redl, Christian & Haas, Reinhard & Huber, Claus & Böhm, Bernhard, 2009. "Price formation in electricity forward markets and the relevance of systematic forecast errors," Energy Economics, Elsevier, vol. 31(3), pages 356-364, May.
- Chevillon, Guillaume & Rifflart, Christine, 2007.
"Physical Market Determinants of the Price of Crude Oil and the Market Premium,"
ESSEC Working Papers
DR 07020, ESSEC Research Center, ESSEC Business School.
- Chevillon, Guillaume & Rifflart, Christine, 2009. "Physical market determinants of the price of crude oil and the market premium," Energy Economics, Elsevier, vol. 31(4), pages 537-549, July.
- Paul L. Joskow & Edward Kohn, 2002.
"A Quantitative Analysis of Pricing Behavior in California's Wholesale Electricity Market During Summer 2000,"
The Energy Journal,
International Association for Energy Economics, vol. 0(Number 4), pages 1-35.
- Paul Joskow & Edward Kahn, 2001. "A Quantitative Analysis of Pricing Behavior in California's Wholesale Electricity Market During Summer 2000," NBER Working Papers 8157, National Bureau of Economic Research, Inc.
- Joskow, P. & Edward Kahn, 2002. "A Quantitative Analysis of Pricing Behavior In California’s Wholesale Electricity Market During Summer 2000," Cambridge Working Papers in Economics 0211, Faculty of Economics, University of Cambridge.
- Mohammadi, Hassan, 2009. "Electricity prices and fuel costs: Long-run relations and short-run dynamics," Energy Economics, Elsevier, vol. 31(3), pages 503-509, May.
- Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-81, September.
- Colin F. Camerer, 1997. "Progress in Behavioral Game Theory," Journal of Economic Perspectives, American Economic Association, vol. 11(4), pages 167-188, Fall.
- Ghaffari, Ali & Zare, Samaneh, 2009. "A novel algorithm for prediction of crude oil price variation based on soft computing," Energy Economics, Elsevier, vol. 31(4), pages 531-536, July.
- Severin Borenstein & James B. Bushnell & Frank A. Wolak, 2002. "Measuring Market Inefficiencies in California's Restructured Wholesale Electricity Market," American Economic Review, American Economic Association, vol. 92(5), pages 1376-1405, December.
- Robert Wilson, 2002. "Architecture of Power Markets," Econometrica, Econometric Society, vol. 70(4), pages 1299-1340, July.
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