Toyota jidosha kabushiki kaisha (20240278764). ADAPTATION SYSTEM AND ADAPTATION METHOD simplified abstract
Contents
- 1 ADAPTATION SYSTEM AND ADAPTATION METHOD
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 ADAPTATION SYSTEM AND ADAPTATION METHOD - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about the Technology
- 1.13 Original Abstract Submitted
ADAPTATION SYSTEM AND ADAPTATION METHOD
Organization Name
toyota jidosha kabushiki kaisha
Inventor(s)
Akihiro Katayama of Toyota-shi (JP)
Kenichiro Kumada of Nagakute-shi (JP)
ADAPTATION SYSTEM AND ADAPTATION METHOD - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240278764 titled 'ADAPTATION SYSTEM AND ADAPTATION METHOD
Simplified Explanation
The patent application describes a system that performs a learning routine and executes additional processes based on the number of times the routine is executed. It records changes in trials with rewards and optimizes a control map.
- The system executes a second process after a certain number of learning routine executions but before reaching a termination number.
- The second process includes conducting first and second trials and recording changes in trials with larger rewards.
- A third process is executed when the learning routine reaches a specified number of times, calculating summary statistics of changes and reflecting them in a control map for optimization.
Key Features and Innovation
- Adaptive system with multiple processes based on learning routine execution frequency.
- Recording and analyzing changes in trials with rewards for optimization.
- Utilization of summary statistics to optimize a control map.
Potential Applications
The technology can be applied in:
- Machine learning systems
- Adaptive control systems
- Optimization algorithms
Problems Solved
- Efficient learning routine execution
- Optimization of control maps based on trial results
- Enhanced adaptability in systems
Benefits
- Improved system performance
- Enhanced decision-making capabilities
- Streamlined optimization processes
Commercial Applications
- This technology can be utilized in industries such as robotics, automation, and artificial intelligence for enhanced learning and control capabilities.
Prior Art
Readers can explore prior research on adaptive systems, machine learning algorithms, and control optimization techniques for related information.
Frequently Updated Research
Stay updated on advancements in adaptive systems, machine learning, and control optimization for potential improvements in the technology.
Questions about the Technology
What are the potential real-world applications of this adaptive system?
The technology can be applied in various industries such as robotics, automation, and artificial intelligence for improved learning and control processes.
How does the system optimize control maps based on trial results?
The system calculates summary statistics of changes in trials and reflects them in a control map for enhanced optimization.
Original Abstract Submitted
processing circuitry of an adaptation system executes a second process when a number of times of execution of a learning routine is greater than or equal to a specified number of times and less than a termination number of times. the second process performs a first trial and a second trial in each execution of the learning routine, and ends the learning routine by recording, in a storage device, a change in one of the first trial and the second trial in which a reward is larger. the processing circuitry executes a third process when the number of times of execution of the learning routine reaches a specified number of times. the third process is a process of calculating summary statistics of multiple changes and reflecting the summary statistics in a control map to complete optimization of the control map.
