Transformer-based Multi-agent Reinforcement Learning for Separation Assurance in Structured and Unstructured Airspaces

This article discusses the application of transformer-based multi-agent reinforcement learning to solve the problem of separation assurance in airspaces. It likely proposes a novel approach to air traffic management, leveraging the strengths of transformers and reinforcement learning.

• •Applies transformer-based multi-agent reinforcement learning.
• •Focuses on separation assurance in airspaces.
• •Addresses both structured and unstructured airspaces.