In this paper we study a dynamic multiple access in distributed wireless networks with random number of users. We apply evolutionary game theoretic analysis to solve several problems: (a) We address the stability of Aloha-like systems with finitely many power levels. Specifically, we consider very large number of receivers distributed in several locations. Each of them receives packets from random number of users accessing the resource using Aloha-like algorithms. We provide an explicit expression for equilibria, correlated evolutionarily stable strategies, and prove some asymptotic stability results. (b) We apply correlation mechanism and evaluate the performance of random medium access when saturated users interact through interference. We introduce the benefit of correlation (BoC) to measure the gap between the probability of success at correlated evolutionarily stable strategies and the worst probability of success of evolutionarily stable strategies. We show that if only two power levels are available, the correlation mechanism reduces considerably the interference and the number of collisions. Moreover, the correlation mechanism is stable in long-term under several classes of bio-inspired evolutionary game dynamics. (c) Surprisingly, when the number of strategies is at least three, the correlation mechanisms do not improve the probability of success.