Invention Grant
- Patent Title: Recurrent environment predictors
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Application No.: US16893565Application Date: 2020-06-05
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Publication No.: US11200482B2Publication Date: 2021-12-14
- Inventor: Daniel Pieter Wierstra , Shakir Mohamed , Silvia Chiappa , Sebastien Henri Andre Racaniere
- Applicant: DeepMind Technologies Limited
- Applicant Address: GB London
- Assignee: DeepMind Technologies Limited
- Current Assignee: DeepMind Technologies Limited
- Current Assignee Address: GB London
- Agency: Fish & Richardson P.C.
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06N3/08 ; G06N3/00

Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for environment simulation. In one aspect, a system comprises a recurrent neural network configured to, at each of a plurality of time steps, receive a preceding action for a preceding time step, update a preceding initial hidden state of the recurrent neural network from the preceding time step using the preceding action, update a preceding cell state of the recurrent neural network from the preceding time step using at least the initial hidden state for the time step, and determine a final hidden state for the time step using the cell state for the time step. The system further comprises a decoder neural network configured to receive the final hidden state for the time step and process the final hidden state to generate a predicted observation characterizing a predicted state of the environment at the time step.
Public/Granted literature
- US20200342289A1 RECURRENT ENVIRONMENT PREDICTORS Public/Granted day:2020-10-29
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