18384178. LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM simplified abstract (NEC Corporation)
Contents
- 1 LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM
Organization Name
Inventor(s)
LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18384178 titled 'LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM
Simplified Explanation
The abstract of the patent application describes a learning device that acquires a next state and a reward, calculates a state value, generates a shaped reward, updates a policy, and updates parameters.
- The acquisition means acquires a next state and a reward as a result of an action.
- The calculation means calculates a state value of the next state using the next state and a state value function of a teacher model.
- The generation means generates a shaped reward from the state value.
- The policy updating means updates a policy of a student model using the shaped reward and a discount factor of the student model to be learned.
- The parameter updating means updates the discount factor.
Potential Applications
This technology could be applied in:
- Reinforcement learning systems
- Autonomous robots
- Gaming AI development
Problems Solved
This technology helps in:
- Improving learning efficiency
- Enhancing decision-making processes
- Optimizing resource allocation
Benefits
The benefits of this technology include:
- Faster learning rates
- More accurate decision-making
- Increased performance in complex environments
Potential Commercial Applications
Potential commercial applications of this technology include:
- Educational software
- Financial trading algorithms
- Healthcare diagnostics systems
Possible Prior Art
One possible prior art for this technology could be:
- Q-learning algorithms in reinforcement learning
Unanswered Questions
How does this technology handle complex and dynamic environments?
This technology utilizes a shaped reward generation process to adapt to changing environments and optimize decision-making.
What are the limitations of this technology in real-world applications?
The limitations of this technology may include scalability issues in large-scale systems and potential biases in the learning process.
Original Abstract Submitted
In a learning device, the acquisition means acquires a next state and a reward as a result of an action. The calculation means calculates a state value of the next state using the next state and a state value function of a teacher model. The generation means generates a shaped reward from the state value. The policy updating means updates a policy of a student model using the shaped reward and a discount factor of the student model to be leaned. The parameter updating means updates the discount factor.
