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A new hybrid framework based on game theory and dynamic programming (DP) with random demands and prices is proposed for studying the impacts of regulatory interventions on the dynamics of investment in power generation in electricity markets. In our approach, using Markov chains, the electric demand and growth of fuel prices have been modeled. DP has been used for solving the generation expansion planning (GEP) problem. Investment strategies of other investors in the market are modeled as constraints. The income of the investor is calculated by modeling strategic interactions among market players in the spot energy market. The Cournot game concept has been applied and the Nash equilibrium is calculated for each state and stage of DP. Simulation results confirm that the proposed framework is an appropriate decision-support tool that provides useful information about dynamics of investment.