The industrial Wave Energy Converters (WEC) have evolved into complex multi-generator designs, but a lack of effective control has limited their potential for higher energy capture efficiency. The Multi-Agent Reinforcement Learning (MARL) controller can handle these complexities and support multiple objectives of energy capture efficiency, reduction of structural stress, and proactive protection against high waves. However, even with well-trained agent algorithms like Proximal Policy Optimizatio…