DISTRIBUTED TRAINING USING ACTOR-CRITIC REINFORCEMENT LEARNING WITH OFF-POLICY CORRECTION FACTORS

Patent №

US 11,593,646

Granted

2023-02-28

Filed 2020

Owner

DEEPMIND TECHNOLOGIES LIMITED

AI components

6

ml · vision · speech · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

16767049

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an action selection neural network used to select actions to be performed by an agent interacting with an environment. In one aspect, a system comprises a plurality of actor computing units and a plurality of learner computing units. The actor computing units generate experience tuple trajectories that are used by the learner computing units to update learner action selection neural network parameters using a reinforcement learning technique. The reinforcement learning technique may be an off-policy actor critic reinforcement learning technique.

Machine learningVisionSpeechKnowledge representationPlanningAI hardwareG06N 3/084G06N 3/092G06N 3/006G06N 3/0442G06N 3/045G06N 3/0464G06N 3/063G06N 3/098+1 more

AI classification

Machine learning1.00
Planning1.00
Knowledge representation1.00
AI hardware1.00
Vision0.97
Speech0.93
Natural language0.01
Evolutionary computation0.00

Ownership

DEEPMIND TECHNOLOGIES LIMITED

assignment · 531910855

Assignors

SOYER, HUBERT JOSEF, ESPEHOLT, LASSE, SIMONYAN, KAREN, DORON, YOTAM, FIROIU, VLAD, MNIH, VOLODYMYR, KAVUKCUOGLU, KORAY, MUNOS, REMI, WARD, THOMAS, HARLEY, TIMOTHY JAMES ALEXANDER, DUNNING, IAIN ROBERT

On an employer assignment, the assignors are typically the inventors.

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