A report on the Cooperative Multi-Agent Systems Decision-Making and Learning: From Individual Needs to Swarm Intelligence workshop, which took place at AAAI 2024, on 26 February. With the tremendous growth of AI technology, robotics, IoT, and high-speed wireless sensor networks (like 5G) in recent years, an artificial ecosystem has been formed, termed artificial social systems, that involves AI agents from software entities to hardware devices. How to integrate artificial social systems into human society so that they coexist harmoniously is a critical issue. At this point, rational decision-making and efficient learning from multi-agent systems (MAS) interactions are the preconditions to guarantee multi-agents working safely, balancing the group utilities and system costs in the long term, and satisfying group members' needs in their cooperation. From the cognitive modeling perspective, it may provide a more realistic basis for understanding cooperative multi-agent interactions by embodying realistic constraints, capabilities, and tendencies of individual agents in their interactions, including physical and social environments.