18550136. INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING METHOD, AND PROGRAM simplified abstract (Sony Group Corporation)
Contents
- 1 INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING METHOD, AND PROGRAM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING METHOD, AND 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 Unanswered Questions
- 1.11 Original Abstract Submitted
INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING METHOD, AND PROGRAM
Organization Name
Inventor(s)
YOSHIYUKI Kobayashi of TOKYO (JP)
INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING METHOD, AND PROGRAM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18550136 titled 'INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING METHOD, AND PROGRAM
Simplified Explanation
The present technology involves an information processing system that can determine execution of learning without relying on external instruction inputs. The system uses environmental information and a learning model obtained through learning to evaluate actions.
- The information processing system includes an error detection unit to determine the difference between newly input environmental information or evaluation function and existing information, and a learning unit to update the learning model based on this difference and the reward obtained for an action through evaluation.
- The system can be applied to information processing systems that require autonomous learning capabilities.
Potential Applications
The technology can be applied in various fields such as robotics, autonomous vehicles, and artificial intelligence systems that require autonomous decision-making capabilities.
Problems Solved
1. Eliminates the need for external instruction inputs for learning. 2. Improves the efficiency and accuracy of decision-making processes in information processing systems.
Benefits
1. Enhanced autonomous learning capabilities. 2. Improved adaptability to changing environments. 3. Increased efficiency in decision-making processes.
Potential Commercial Applications
Optimizing autonomous systems in industries such as manufacturing, healthcare, and transportation for improved performance and decision-making capabilities.
Possible Prior Art
One possible prior art could be reinforcement learning algorithms used in artificial intelligence systems for autonomous decision-making processes.
Unanswered Questions
How does the error detection unit determine the magnitude of the differential between input and existing information?
The error detection unit uses mathematical algorithms to calculate the difference between newly input environmental information or evaluation function and the existing information.
What are the specific parameters used in the evaluation function for determining the reward obtained for an action?
The evaluation function may consider factors such as accuracy, efficiency, and effectiveness of the action taken to calculate the reward obtained.
Original Abstract Submitted
The present technology relates to an information processing system, an information processing method, and a program that make it possible to determine execution of learning, without relying on external instruction inputs. The information processing system determines an action on the basis of environmental information and a learning model obtained through learning based on an evaluation function for evaluating an action. The information processing system includes an error detection unit configured to determine a magnitude of a differential between the environmental information that has been newly input or the evaluation function that has been newly input and the environmental information that has existed or the evaluation function that has existed and a learning unit configured to update, depending on the magnitude of the differential, the learning model on the basis of the environmental information that has been newly input or the evaluation function that has been newly input and an amount of reward obtained for an action through the evaluation. The present technology can be applied to information processing systems.
