kmock930/MARL-autonomous-vehicle

AI Summary: The task requires re-delivering code changes that were previously committed but seemingly lost due to an accidentally closed issue. The code changes relate to a multi-agent reinforcement learning project for autonomous vehicle navigation, specifically addressing improvements suggested in a previous commit message. The project uses a custom grid-based environment and involves several neural network models (encoder, decoder, policy networks for leader and follower agents).

AI Summary: Refactor a messy multi-agent reinforcement learning (MARL) codebase for autonomous vehicle navigation. This involves modularizing the code, implementing comprehensive unit and integration tests (ideally with pytest), setting up a CI/CD pipeline with at least 80% code coverage, and documenting the refactoring process academically. No functional changes are required; the focus is solely on improving code structure, testability, and maintainability.