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Mixed Autonomy Traffic: A Reinforcement Learning Perspective
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Mixed Autonomy Traffic: A Reinforcement Learning Perspective
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- 1 Intro
- 2 Counterfactual reasoning with • Motivation: Quantify impact of technology on societal systems • Pace of change & complexity is increasing
- 3 Years 2020 to 2049: Mixed autonomy Transportation in the US
- 4 Urban simulation
- 5 Axes of difficulty in mixed autonomy
- 6 Single-lane: dynamical system equil Human driver model
- 7 Challenge: combinatorial number of environn A critical challenge to scaling deep reinforcement learning
- 8 Transfer learning across networ
- 9 Zero-shot transfer
- 10 The road ahead: counterfactual reasoning for societa Motivation Quantity impact of technology on societal systems
- 11 Mixed Autonomy Traffic: A Reinforcement Learning Perspective
