PATENT CLAIM ANALYSIS

Application Number: 15919456
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-09
Patent Classification: ["318", "561000"]

Abstract:
A machine learning device performs machine learning with respect to a servo control device including a velocity feedforward calculation unit. The machine learning device comprises: a state information acquisition unit configured to acquire from the servo control device, state information including at least position error, and combination of coefficients of a transfer function of the velocity feedforward calculation unit; an action information output unit configured to output action information including adjustment information of the combination of coefficients included in the state information, to the servo control device; a reward output unit configured to output a reward value in reinforcement learning based on the position error included in the state information; and a value function updating unit configured to update an action value function on the basis of the reward value output by the reward output unit, the state information, and the action information.

Claim (Index 11):
A machine learning method of a machine learning device that performs machine learning with respect to a servo control device comprising a velocity feedforward calculation unit configured to create a velocity feedforward value on the basis of a position command, the machine learning method comprising:\n acquiring from the servo control device, state information including a servo state including at least position error, and combination of coefficients of a transfer function of the velocity feedforward calculation unit by causing the servo control device to execute a predetermined machining program; outputting action information including adjustment information of the combination of coefficients included in the state information, to the servo control device; and updating an action value function on the basis of a reward value in reinforcement learning, based on the position error included in the state information, the state information, and the action information.

Metadata:
- Claim Count in Document: 25.0
- Percentile: 90.0
- Lexical Diversity: 2.85185
- Patent Class: 318.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15628641', '15838510', '15368753', '13803453', '15290253']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6721105187939194
- 35 USC 102 Novelty (BERT): 0.4806120877280596
- Combined Prediction Score: 0.6529606756873334
- Mean Citation Score: 212.57303
- Max Citation Score: 220.89268
- Similarity Product: 174.53375315965653

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

Dataset: test