Learning Device Continuous Configuration via Reflex Patterns
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Solution Overview
Problem
Computer programmers face inefficiencies and costs when reconfiguring programmable devices for new behaviors, as they require expertise in writing complex code and often involve hiring consultants, making the process time-consuming and costly.
Innovation Solution
The development of systems and methods for continuous configuration of learning devices that allow them to observe and correlate events to trigger actions, enabling intuitive training and configuration without the need for expert programming, using reflexes with trigger, correction, and reward patterns to adjust and create new behaviors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If expert programmers are used to reprogram programmable devices for new behaviors, then the device can perform new tasks, but the process becomes time-consuming and costly
Solution Approach 1:
The learning device autonomously configures itself to perform new behaviors by observing events and automatically creating reflexes, eliminating the need for expert programmers. The device monitors events, identifies trigger patterns, and self-programmes reflexes with appropriate actions, thereby resolving the contradiction between adaptability and reprogramming time.
Solution Approach 2:
The patent introduces an intermediary learning mechanism that translates observed events into configurable reflexes automatically. This intermediary layer between raw events and device behavior enables non-experts to configure new behaviors simply by observing and training the device, without needing to write complex code.
2Adaptability or versatility
If expert programmers are hired to reprogram devices, then new behaviors can be implemented, but costs increase due to consulting fees or staff requirements
Solution Approach 1:
The learning device performs its own configuration by automatically analyzing events and generating appropriate reflexes, eliminating the need to hire expert programmers or consultants. This self-service capability directly reduces configuration costs while maintaining full adaptability for implementing new behaviors.
3Adaptability or versatility
If complex code is written through programmer interfaces, then device reconfiguration is achieved, but the process becomes arduous and requires specialized expertise
Solution Approach 1:
The patent introduces an intermediary event-driven learning mechanism that replaces complex programmer interfaces with simple event observation and automatic reflex creation. Users can configure new behaviors by providing training events rather than writing code, making the process intuitive and accessible to non-programmers.
Solution Approach 2:
The patent replaces the mechanical process of manual code writing and programming interface interaction with an automated information processing system. The learning device automatically processes observed events, identifies patterns, and generates configuration code, substituting the manual mechanical programming process with automated intelligent processing.
4Adaptability or versatility
If traditional reprogramming methods are used, then device behavior changes are achieved, but immediate reconfiguration is rarely accomplished due to scheduling experts
Solution Approach 1:
The learning device immediately configures itself to perform new behaviors by autonomously processing observed events and creating reflexes in real-time. This eliminates the scheduling delays inherent in traditional methods that require expert availability, enabling immediate reconfiguration whenever new behaviors are needed.
Data Source
AI summary
An embodiment method for continuous configuration of learning devices includes operations for storing, by a learning device within a decentralized system of a plurality of learning devices, events obtained while in a monitoring mode, activating a triggered mode for a reflex when at least one of the stored events corresponds to a trigger pattern, determining whether the reflex has a trigger weight exceeding a trigger weight threshold, conducting the predetermined action associated with the reflex when the trigger weight exceeds the trigger weight threshold, obtaining at least one additional event while in the triggered mode, adjusting the trigger weight of the reflex when the at least one additional event corresponds to a correction pattern or a reward pattern occurring in response to conducting the predetermined action, and creating a second reflex when the at least one additional event does not correspond to a known pattern.