18544651. OPTIMIZATION APPARATUS, OPTIMIZATION METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM STORING OPTIMIZATION PROGRAM simplified abstract (NEC Corporation)
Contents
- 1 OPTIMIZATION APPARATUS, OPTIMIZATION METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM STORING OPTIMIZATION PROGRAM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 OPTIMIZATION APPARATUS, OPTIMIZATION METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM STORING OPTIMIZATION PROGRAM - 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 Original Abstract Submitted
OPTIMIZATION APPARATUS, OPTIMIZATION METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM STORING OPTIMIZATION PROGRAM
Organization Name
Inventor(s)
OPTIMIZATION APPARATUS, OPTIMIZATION METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM STORING OPTIMIZATION PROGRAM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18544651 titled 'OPTIMIZATION APPARATUS, OPTIMIZATION METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM STORING OPTIMIZATION PROGRAM
Simplified Explanation
The optimization apparatus described in the abstract of the patent application involves selecting correction values, acquiring results of policy execution, calculating estimated values, updating probability distributions, and determining policies for future rounds based on the updated distributions.
- Selection unit chooses correction values from convex hulls of a policy set.
- Acquisition unit gathers results of executing policies in different rounds.
- Calculation unit estimates loss vector values based on execution results and correction values.
- Update unit adjusts probability distributions based on estimated values.
- Determination unit decides on policies for upcoming rounds using the updated distributions.
Potential Applications
The technology described in this patent application could be applied in various fields such as finance, logistics, and artificial intelligence for optimizing decision-making processes.
Problems Solved
This technology helps in improving the efficiency and effectiveness of decision-making by utilizing correction values and updating probability distributions based on execution results.
Benefits
The benefits of this technology include enhanced decision-making capabilities, increased accuracy in predicting outcomes, and improved overall performance in various applications.
Potential Commercial Applications
One potential commercial application of this technology could be in the development of advanced optimization software for businesses looking to streamline their operations and improve decision-making processes.
Possible Prior Art
One possible prior art for this technology could be related to optimization algorithms used in machine learning and artificial intelligence systems to improve decision-making processes.
What are the specific industries that could benefit from this technology?
Various industries such as finance, healthcare, supply chain management, and autonomous systems could benefit from the optimization technology described in this patent application.
How does this technology compare to existing optimization methods?
This technology stands out by incorporating correction values and updating probability distributions to enhance decision-making processes, which can lead to more accurate and efficient outcomes compared to traditional optimization methods.
Original Abstract Submitted
An optimization apparatus includes: a selection unit that selects, as a correction value, an element having a magnitude equal to or smaller than a predetermined value from among convex hulls of a policy set; an acquisition unit that acquires a result of execution of a second policy executed in a second round, the second round being a round a predetermined round before a first round for executing a first policy that is determined from among the policy set; a calculation unit that calculates an estimated value of a loss vector in the execution of the policy based on the result of the execution and the correction value selected in the second round; an update unit that updates a first probability distribution based on the estimated value; and a determination unit that determines a policy for a next round based on the updated first probability distribution.
