Deep Reinforcement Learning for Driving Policy

Описание к видео Deep Reinforcement Learning for Driving Policy

Autonomous driving is a multi-agent setting where the host vehicle must apply sophisticated negotiation skills with other road users when overtaking, giving way, merging, taking left and right turns and while pushing ahead in unstructured urban roadways.

Since there are many possible scenarios, manually tackling all possible cases will likely yield a too simplistic policy.

Moreover, one must balance between unexpected behavior of other drivers/pedestrians and at the same time not to be too defensive so that normal traffic flow is maintained.

Symposium on "Information, Control, and Learning" at The Hebrew University of Jerusalem.

By Prof. Shai Shalev Shwartz, VP Technologies of Mobileye
and professor of computer science at The Hebrew University of Jerusalem.

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