Nec corporation (20240135394). OPTIMIZATION APPARATUS, OPTIMIZATION METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM STORING OPTIMIZATION PROGRAM simplified abstract
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 20240135394 titled 'OPTIMIZATION APPARATUS, OPTIMIZATION METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM STORING OPTIMIZATION PROGRAM
Simplified Explanation
The optimization apparatus described in the abstract aims to improve decision-making processes by selecting correction values, acquiring results of policy executions, calculating estimated losses, 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 a second policy in a predetermined round.
- Calculation unit estimates loss vector based on execution results and correction values.
- Update unit adjusts probability distributions based on estimated values.
- Determination unit selects policies for the next round using the updated distributions.
Potential Applications
The technology can be applied in various fields such as finance, logistics, and resource allocation to optimize decision-making processes and improve overall efficiency.
Problems Solved
1. Enhances decision-making by incorporating correction values and estimated losses. 2. Streamlines policy selection for future rounds based on updated probability distributions.
Benefits
1. Increased efficiency in decision-making processes. 2. Improved accuracy in policy selection for future rounds. 3. Enhanced optimization of resources and outcomes.
Potential Commercial Applications
"Optimization Apparatus for Decision-Making Processes" can be utilized in industries such as finance, supply chain management, and healthcare to improve operational efficiency and maximize outcomes.
Possible Prior Art
There may be prior art related to optimization algorithms and decision-making processes in various industries. However, specific prior art related to the described apparatus would need to be researched further.
Unanswered Questions
How does the apparatus handle uncertainty in decision-making processes?
The abstract does not provide details on how the apparatus addresses uncertainty in decision-making scenarios. It would be essential to understand how the technology deals with unpredictable factors and their impact on policy selection.
What data sources are used to inform the decision-making process?
The abstract does not specify the data sources utilized by the optimization apparatus. Understanding the sources of information and their reliability would be crucial in assessing the effectiveness of the technology.
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.
