Invention Grant
- Patent Title: Noisy neural network layers with noise parameters
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Application No.: US17020248Application Date: 2020-09-14
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Publication No.: US11977983B2Publication Date: 2024-05-07
- Inventor: Mohammad Gheshlaghi Azar , Meire Fortunato , Bilal Piot , Olivier Claude Pietquin , Jacob Lee Menick , Volodymyr Mnih , Charles Blundell , Remi Munos
- 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: G06N3/084
- IPC: G06N3/084 ; G06N3/044

Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting an action to be performed by a reinforcement learning agent. The method includes obtaining an observation characterizing a current state of an environment. For each layer parameter of each noisy layer of a neural network, a respective noise value is determined. For each layer parameter of each noisy layer, a noisy current value for the layer parameter is determined from a current value of the layer parameter, a current value of a corresponding noise parameter, and the noise value. A network input including the observation is processed using the neural network in accordance with the noisy current values to generate a network output for the network input. An action is selected from a set of possible actions to be performed by the agent in response to the observation using the network output.
Public/Granted literature
- US20210065012A1 NOISY NEURAL NETWORK LAYERS WITH NOISE PARAMETERS Public/Granted day:2021-03-04
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