View source for 18348687. Reinforcement Learning with Information Retrieval Feedback (Google LLC)

=Reinforcement Learning with Information Retrieval Feedback=


==Organization Name==

[[:Category:Google LLC|Google LLC]]


[[Category:Google LLC]]

==Inventor(s)==

[[:Category:Hyun Jin Park of Palo Alto CA (US)|Hyun Jin Park of Palo Alto CA (US)]][[Category:Hyun Jin Park of Palo Alto CA (US)]]

[[:Category:Dongseong Hwang of Kirkland WA (US)|Dongseong Hwang of Kirkland WA (US)]][[Category:Dongseong Hwang of Kirkland WA (US)]]

[[:Category:Chang Wan Ryu of Mountain View CA (US)|Chang Wan Ryu of Mountain View CA (US)]][[Category:Chang Wan Ryu of Mountain View CA (US)]]

==Reinforcement Learning with Information Retrieval Feedback==


This abstract first appeared for US patent application 18348687 titled 'Reinforcement Learning with Information Retrieval Feedback




==Original Abstract Submitted==

In one example aspect, the present disclosure provides an example computer-implemented method for generating feedback signals for training a machine-learned agent model. The example method can include obtaining an output of a machine-learned agent model, the output including a next state feature generated by the machine-learned agent model based on a sequence of preceding states. The example method can include processing, using a machine-learned reward model, the output and the sequence of preceding states to generate a quality indicator indicating a quality of the next state feature in view of the preceding states. The machine-learned reward model could be trained by retrieving reference data from a reference data source and computing one or more quality indicators in view of a respective training input and output(s), and the reference data. The example method can include outputting the quality indicator to a model trainer for updating the machine-learned agent model.



[[Category:G06N20/00]]
[[Category:CPC_G06N20/00]]