PATENT CLAIM ANALYSIS

Application Number: 16127716
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-04
Patent Classification: ["706", "025000"]

Abstract:
Exemplary embodiments can maximize long-term value in a machine learning system. The system may employ an offline training process and an online training process. In the offline training process, an initial policy is learned to provide a warm start to the online training process. In the online training process, the system applies concurrent reinforcement learning across multiple environments, with the goal of learning efficient policies in real time from in-flight user data in one environment, and applying the learned policies to other environments. With the combination of offline training and online training, the system is able to improve initial performance through the warm start, while adapting to a changing context through concurrent reinforcement learning.

Claim (Index 23):
The apparatus of  claim 21 , wherein the dynamics further comprise a plurality of next states and a probability of transitioning to each of the next states given that the action is taken.

Metadata:
- Claim Count in Document: 59.0
- Percentile: 97.0
- Lexical Diversity: 1.98413
- Patent Class: 706.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15997371', '15723539', '15986037', '15897263', '16023949']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.384680563316355
- 35 USC 102 Novelty (BERT): 0.5063653917253733
- Combined Prediction Score: 0.3968490461572568
- Mean Citation Score: 180.807792
- Max Citation Score: 190.55603
- Similarity Product: 109.14729869003534

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

Dataset: test