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This paper presents a coevolutionary algorithm named cooperative coevolutionary invasive weed optimization (CCIWO) and investigates its performance for global optimization of functions with numerous local optima and also Nash equilibrium (NE) search for games. Ability of CCIWO for function optimization is tested through a set of common benchmarks of stochastic optimization, and reported results are...
A method based on the novel optimization algorithm of Invasive Weed colonization Optimization (IWO) is used to study electricity market dynamics. Dynamics of such a multi agent system is analyzed using aspects both from Game theory and IWO. The method is integrated with a power system simulator to consider all the constraints of a realistic power system to make sure that the results are reliable....
Classical game theory is concerned with how rational players make decisions when they are faced with known payoffs. In the past decade, fuzzy logic has been widely used to manage uncertainties in games. In this paper, we employ fuzzy logic to determine the priority of a payoff to other payoffs. A new term is introduced to measure the preference of one payoff to others. By this means a fuzzy preference...
This paper presents the implementation of an intelligent pass strategy for soccer robots using fuzzy logic. The proposed strategy calculates pass confidence and detects the best destination robot and best position for passing. The most important factors of a proper pass are detected and are deployed to construct the inputs of fuzzy system. The rule base of the fuzzy system is extracted by utilizing...
In this paper, an analytical comparison is done between dynamic programming and reinforcement learning methods in dynamic two-player games. The emphasis is on the large number of states and actions available for each player and different conflictive optimization objectives of these games that make them complicated in modeling and analysis. Optimization and decision making is done through quantifying...
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