Traffic control with reinforcement learning

An action recommendation system uses reinforcement learning that provides a next action recommendation to a traffic controller to give to a vehicle pilot such as an aircraft pilot. The action recommendation system uses data of past human actions to create a reinforcement learning model and then uses...

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Bibliographische Detailangaben
Hauptverfasser:	Ganti, Raghu Kiran, Chu, Linsong, Rao, Venkatesh Ashok Rao, Srivatsa, Mudhakar
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING PHYSICS SIGNALLING TRAFFIC CONTROL SYSTEMS
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Beschreibung
Zusammenfassung:	An action recommendation system uses reinforcement learning that provides a next action recommendation to a traffic controller to give to a vehicle pilot such as an aircraft pilot. The action recommendation system uses data of past human actions to create a reinforcement learning model and then uses the reinforcement learning model with current ABS-B data to provide the next action recommendation to the traffic controller. The action recommendation system may use an anisotropic reward function and may also include an expanding state space module that uses a non-uniform granularity of the state space.