An algorithm for approximately solving the maximum clique is presented which uses relaxation labeling neural network techniques, focusing on the continuous problem formulation: maximize a quadratic form over the standard simplex. We employ somewhat surprising connections of the latter problem with dynamic principles of evolutionary game theory, and give a detailed report on our numerical experiences with the method proposed.
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