• MARL has become a key research area with applications in autonomous driving, drone collaboration, smart cities, smart grids, and robotic cooperation.
• The reward function is fundamental in MARL, providing feedback that guides agents to optimal decisions; careful design is essential for fostering cooperation.
• Cooperative objective optimization ensures alignment of individual strategies with collective goals, enabling efficient collaboration and adaptability.
• The review highlights simulation environments and discusses future trends, offering a roadmap for continued research in cooperative MARL.