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cs.LG2020
Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways
Branka Mirchevska, Maria Hügle, Gabriel Kalweit +2
Well-established optimization-based methods can guarantee an optimal trajectory for a short optimization horizon, typically no longer than a few seconds. As a result, choosing the…
cs.LG2019
Dynamic Input for Deep Reinforcement Learning in Autonomous Driving
Maria Hügle, Gabriel Kalweit, Branka Mirchevska +2
In many real-world decision making problems, reaching an optimal decision requires taking into account a variable number of objects around the agent. Autonomous driving is a domain…