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The use of an agent based simulation platform for market structure policy simulations in a restructured electricity markets reveal subtle insights with respect to the limited exercise of market power in situations where more conventional oligopoly models would suggest greater exploitation. The paper describes a detailed market simulation platform with agent strategies emerging as a result of simple reinforcement learning on both profit and capacity utilization. An example applied to addressing the evolution of some of the Italian market structure issues is described.