Traffic Lego Blocks
Cathy discusses the foundational approach to reinforcement learning in traffic scenarios, emphasizing the importance of designing simple environments, or "traffic lego blocks," to study vehicle interactions. She highlights the intricate process of defining the Markov decision process components, including states, actions, and rewards, while considering practical limitations on vehicle observations. The ultimate aim is to scale these insights to complex city networks, balancing efficiency with human factors.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Simulating the Future of Traffic with RL w/ Cathy Wu - #362
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