Matchmaking in Electronic Markets: An Agent-Based Approach Towards Matchmaking in Electronic Negotiations (Lecture Notes in Computer Science, 2882.)
Design of coordination strategies in multiagent systems via genetic fuzzy systems
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Mascem: A Multiagent System That Simulates Competitive Electricity Markets
IEEE Intelligent Systems
Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics (Handbook of Computational Economics)
Genetic fuzzy systems to evolve interaction strategies in multiagent systems: Research Articles
International Journal of Intelligent Systems
A multi agent based simulator for brazilian wholesale electricity energy market
IBERAMIA-SBIA'06 Proceedings of the 2nd international joint conference, and Proceedings of the 10th Ibero-American Conference on AI 18th Brazilian conference on Advances in Artificial Intelligence
IEEE Transactions on Evolutionary Computation
Environmental Modelling & Software
| Hi-index | 0.00 |
This paper suggests a multiagent system (MAS) approach for market simulation. This is achieved through analysis, modeling, implementation and simulation of artificial markets populated by software agents that represent economic self interested agents. Software agents are the constructs of a complex system, an artificial market that model a real existing market or an outline of a market design. The interest in simulating a market is multiple: exploiting existing market rules, searching for market design flaws and loopholes, and supporting decision making during a market mechanism design process. The main aim of the suggested approach is to analyze the behavior that emerges from the interaction of self interested agents acting in an artificial market. AEMAS (Artificial Economy MultiAgent System), a multiagent system architecture inspired by the Market Oriented Programming (MOP) approach is defined. In different economical sectors, e.g. energy markets, there is no consensus about which structures lead to social welfare maximization outcomes. An approach to find adequate architectures allows different market structure instances to be created and simulated, to ease the design and analysis of alternative structures. These alternatives can then be compared and potential design flaws eventually risen by simulation identified. Taking the electricity market as an example, two instances of the proposed architecture are presented, corresponding to the centralized dispatch arrangement common to non restructured markets, and the auction based pool, common to restructured markets.