How can I build efficient MARL-based traffic signal control systems?
PyTSC: A Unified Platform for Multi-Agent Reinforcement Learning in Traffic Signal Control
October 25, 2024
https://arxiv.org/pdf/2410.18202- This paper introduces PyTSC, a new open-source platform for traffic signal control research using multi-agent reinforcement learning (MARL).
- PyTSC offers a unified API to connect with popular traffic simulators like SUMO and CityFlow, making it easier to develop and test MARL algorithms.
- PyTSC is specifically designed to support centralized training and decentralized execution (CTDE), a key paradigm for real-world multi-agent systems, where agents (traffic signals) learn collaboratively but act independently.
- While the paper focuses on traffic signal control, PyTSC's design and capabilities, especially its support for CTDE, make it relevant for developing and experimenting with LLM-based multi-agent systems in a simulated environment.