LLNL computer scientists explore deep learning to improve efficiency of ride-hailing and autonomous electric vehicles

Computer scientists at Lawrence Livermore National Laboratory are preparing the future of commuter traffic by applying Deep Reinforcement Learning — the same kind of goal-driven algorithms that have defeated video game experts and world champions in the strategy game Go — to determine the most efficient strategy for charging and driving electric vehicles used for ride-sharing services.

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UIC Urban Forum to explore the growth, potential impact and future of autonomous vehicles

The University of Illinois at Chicago’s 2019 Urban Forum, titled “Are we there yet? The myths and realities of autonomous vehicles,” will examine the questions and uncertainties surrounding not only the societal and legislative impact of autonomous vehicles, but also the technological advances needed for these vehicles to proliferate.

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