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Hybridizing agent-based paradigm with evolutionary computation can enhance the field of metaheuristics in a significant way, giving to usually passive individuals autonomy and capabilities of perception and interaction with other ones, treating them as agents. In the paper as a follow-up to the previous research, an evolutionary multi-agent system (EMAS) is examined in difficult discrete benchmark problems. As a means for comparison, classical evolutionary algorithm (constructed along withdoi:10.1016/j.procs.2014.05.093 fatcat:i3qrrsbh75gq7pfhfot4q7ewam