GRASP: Gradient Realignment via Active Shared Perception for Multi-Agent Collaborative Optimization

1. 1Identify non-stationarity in multi-agent systems
2. 2Implement GRASP to enable active shared perception among agents
3. 3Update policies using gradient realignment to mitigate environmental fluctuations
4. 4Evaluate the performance of GRASP in comparison to existing approaches like CTDE

This research benefits AI engineers and ML researchers working on multi-agent systems, as it provides a new framework for optimizing collaborative behavior

💡 Active shared perception can help mitigate non-stationarity in multi-agent systems

🤖 Introducing GRASP: a new approach for multi-agent collaborative optimization via active shared perception!