Dynamic pricing may be applied in an online ride-hailing platform. Information may be obtained. The information may include a set of pricing candidates and an initial status of a ride-hailing platform. The set of pricing candidates may be updated based on the initial status of the ride-hailing platform to minimize a cross-entropy between the set of pricing candidates and a target pricing policy that maximizes a total income of the ride-hailing platform. A price for at least one current trip request on the ride-hailing platform may be generated based on the updated set of pricing candidates.
MODEL-BASED DEEP REINFORCEMENT LEARNING FOR DYNAMIC PRICING IN ONLINE RIDE-HAILING PLATFORM