Cognitive Community Map for Intermodel Collaboration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current cognitive models lack a standardized approach to leverage the services of other models, hindering their ability to automatically discover and collaborate effectively, which limits their decision-making capabilities and output quality.
Innovation Solution
A cognitive community map is created by compiling information about other cognitive instances' capabilities, allowing a first cognitive instance to identify and utilize suitable peers for assistance based on specific requirements, using a map-based approach that dynamically updates and prioritizes available expertise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cognitive models operate independently without standardized collaboration protocols, then each model maintains its own decision-making autonomy, but the system loses access to diverse cognitive perspectives and knowledge bases that could improve decision quality
Solution Approach 1:
The patent implements a universal discovery protocol that enables any cognitive model instance to discover and collaborate with other cognitive models regardless of their specific type or implementation. The cognitive community map serves as a multi-functional data structure that stores capability information, identity details, and collaboration metadata, allowing diverse cognitive models to interact through a standardized interface while maintaining their individual decision-making autonomy
Solution Approach 2:
The patent introduces an intermediary discovery mechanism that mediates between independent cognitive models. The cognitive community map acts as an intermediary data structure that facilitates interaction by storing and organizing capability information from multiple cognitive models, enabling them to discover and leverage each other's strengths without direct complex peer-to-peer coordination
2Productivity
If cognitive models automatically discover and collaborate with other models, then the system leverages diverse knowledge bases for better decisions, but the models must invest resources in discovery protocols and capability mapping
Solution Approach 1:
The patent applies preliminary action by having cognitive models pre-register their capability profiles in the cognitive community map before actual collaboration occurs. This advance preparation stores essential information about what each model can do, eliminating the need for complex real-time capability negotiation during problem-solving and reducing computational overhead when collaboration is actually needed
3Measurement precision
If cognitive models maintain detailed capability profiles and community maps, then the system can make informed decisions about peer selection, but the data storage and management requirements increase
Solution Approach 1:
The patent extracts only the essential capability information needed for effective collaboration into the cognitive community map, rather than storing complete model implementations or all possible data. The capability profiles focus on key functional attributes that enable peer selection and collaboration, removing unnecessary detail while maintaining sufficient precision for informed decision-making
Data Source
AI summary
A first cognitive instance receives information about other cognitive instances and from this compiles a cognitive community map that associates individual ones of the other cognitive instances with specific capabilities of said respective other cognitive instances. The first cognitive instance stores that map in a local memory of the first cognitive instance; and when the first cognitive instance executes a cognitive computing program it checks the cognitive community map for at least one of the specific capabilities relevant for executing that program to address/satisfy a user request that caused the program to execute. In various embodiment these cognitive instances share their respective cognitive capabilities via cognitive capability maps, which may be refreshed in their local memories for example by sending a broadcast message. Thus any given cognitive instance can identify cognitive peers with the capabilities most relevant to assist itself in solving a given problem/request.