The development of deregulated electricity systems around the world has produced the need for simulation systems that are capable of addressing the complexities that arise in the new markets. Agent-based models allow the use of complex adaptive systems approaches that are capable of producing tools or problem solving environments that can address the behavior of each of the participants within the electricity market. The agents in the tools are allowed to establish their own objectives and apply their own decision rules. They can be developed to learn from their previous experiences and change their behavior when future opportunities arise. In this paper, we will argue that the same type of agent-based technology that is used to produce "realistic" agent behavior in agent-based simulation tools at Argonne National Laboratory can also be used to embed these tools in problem solving environments.
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