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>New Findings from Tsinghua University Update Understanding of Networks (Personalized Route Recommendation for Ride-hailing With Deep Inverse Reinforcement Learning and Real-time Traffic Conditions)
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New Findings from Tsinghua University Update Understanding of Networks (Personalized Route Recommendation for Ride-hailing With Deep Inverse Reinforcement Learning and Real-time Traffic Conditions)
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机译:New Findings from Tsinghua University Update Understanding of Networks (Personalized Route Recommendation for Ride-hailing With Deep Inverse Reinforcement Learning and Real-time Traffic Conditions)
By a News Reporter-Staff News Editor at Network Daily News – Current studyresults on Networks have been published. According to news reporting originating in Beijing, People’sRepublic of China, by NewsRx journalists, research stated, “Personalized route recommendation aimsto recommend routes based on users’ route preference.The vast amount of GPS trajectories trackingdriving behavior has made deep learning,especially inverse reinforcement learning (IRL), a popular choicefor personalized route rec-ommendation. However, current IRL studies assume that the traffic condition isstatic andapproximate the expected state visitation frequencies to update the neural network.”
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