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公开(公告)号：US11086674B2
公开(公告)日：2021-08-10
申请号：US16423082
申请日：2019-05-27
申请人： ROYAL BANK OF CANADA
发明人： Hasham Burhani , Zichang Long , Jonathan Cupillari
摘要： A system for reinforcement learning in a dynamic resource environment includes at least one memory and at least one processor configured to provide an electronic resource environment comprising: a matching engine and the resource generating agent configured for: obtaining from a historical data processing task database a plurality of historical data processing tasks, each historical data processing task including respective task resource requirement data; for a historical data processing task of the plurality of historical data processing tasks, generating layers of data processing tasks wherein a first layer data processing task has an incremental variant in its resource requirement data relative to resource requirement data for a second layer data processing task; and providing the layers of data processing tasks for matching by the machine engine.
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公开(公告)号：US11715017B2
公开(公告)日：2023-08-01
申请号：US16426196
申请日：2019-05-30
申请人： ROYAL BANK OF CANADA
发明人： Hasham Burhani , Shary Mudassir , Xiao Qi Shi , Connor Lawless , Weiguang Ding
摘要： Systems are methods are provided for training an automated agent. The automated agent maintains a reinforcement learning neural network and generates, according to outputs of the reinforcement learning neural network, signals for communicating resource task requests. First and second task data are received. The task data are processed to compute a first performance metric reflective of performance of the automated agent relative to other entities in a first time interval, and a second performance metric reflective of performance of the automated agent relative to other entities in a second time interval. A reward for the reinforcement learning neural network that reflects a difference between the second performance metric and the first performance metric is computed and provided to the reinforcement learning neural network to train the automated agent.
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公开(公告)号：US11714679B2
公开(公告)日：2023-08-01
申请号：US17380240
申请日：2021-07-20
申请人： ROYAL BANK OF CANADA
发明人： Hasham Burhani , Zichang Long , Jonathan Cupillari
CPC分类号： G06F9/50 , G06F9/48 , G06F9/4881 , G06F9/5005 , G06N5/00 , G06N20/00 , G06Q40/00
摘要： A system for reinforcement learning in a dynamic resource environment includes at least one memory and at least one processor configured to provide an electronic resource environment comprising: a matching engine and the resource generating agent configured for: obtaining from a historical data processing task database a plurality of historical data processing tasks, each historical data processing task including respective task resource requirement data; for a historical data processing task of the plurality of historical data processing tasks, generating layers of data processing tasks wherein a first layer data processing task has an incremental variant in its resource requirement data relative to resource requirement data for a second layer data processing task; and providing the layers of data processing tasks for matching by the machine engine.
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公开(公告)号：US20230061752A1
公开(公告)日：2023-03-02
申请号：US17893302
申请日：2022-08-23
申请人： ROYAL BANK OF CANADA
发明人： Xiao Qi Shi , Hasham Burhani
摘要： Systems, devices, and methods for training an automated agent are disclosed. An automated agent is instantiated. The automated agent includes a reinforcement learning neural network that is trained over a plurality training cycles and provides a policy for generating resource task requests. A learning condition that is expected to impede training of the automated agent during a given training cycle of the plurality of training cycles is detected. In response to the detecting, a disable signal is generated to disable training of the automated agent for at least the given training cycle.
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