EvoMem represents a significant advancement in multi-agent planning by integrating human-like memory mechanisms into artificial intelligence systems. This approach allows agents to better coordinate and reason collectively, improving their ability to solve complex problems. By mimicking aspects of human memory, EvoMem enhances the interaction and decision-making processes among multiple agents. Verified evidence confirms that EvoMem not only improves multi-agent planning but also strengthens agent coordination and reasoning capabilities. These improvements suggest that incorporating cognitive-inspired memory models can lead to more effective AI frameworks in collaborative environments. As a result, EvoMem paves the way for more sophisticated and efficient problem-solving strategies in scenarios requiring multi-agent cooperation. This development marks a promising direction for future AI research focused on collective intelligence.