PATENT CLAIM ANALYSIS

Application Number: 15977923
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-09
Patent Classification: ["706", "025000"]

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for asynchronous deep reinforcement learning. One of the systems includes a plurality of workers, wherein each worker is configured to operate independently of each other worker, and wherein each worker is associated with a respective actor that interacts with a respective replica of the environment during the training of the deep neural network.

Claim (Index 14):
The computer-storage media of  claim 9 , wherein the deep neural network is a Q network that is configured to receive an input observation characterizing an input state of the environment and an input action and to generate a Q value that is an estimate of a long-term reward resulting from the input action being performed when the environment is in the input state, and wherein selecting the current action to be performed by the actor in response to the current observation comprises:\n for each action in the predetermined set of actions, processing the current observation and the action using the deep neural network to generate a Q value for the action in accordance with the current values of the parameters of the deep neural network; and selecting an action from the predetermined set of actions in accordance with the action selection policy for the worker using the Q values for the actions.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 93.0
- Lexical Diversity: 1.58696
- Patent Class: 706.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15016173', '15367094', '15349900', '15977913', '15349894']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4014617749305763
- 35 USC 102 Novelty (BERT): 0.5118457470634978
- Combined Prediction Score: 0.4125001721438685
- Mean Citation Score: 225.962432
- Max Citation Score: 296.19855
- Similarity Product: 209.81858178824183

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test