Semantic Network for Autonomous Agent Coordination
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Solution Overview
Problem
Existing software agents require complex knowledge models that are expensive and difficult to scale, limiting their ability to adapt to changing user needs and requiring significant human intervention for updates, which increases development costs and complexity.
Innovation Solution
A computer system with a semantic network that allows multiple computer-implemented agents to interact and modify the network autonomously, enabling users to modify the network through a user interface without explicit instructions, facilitating collaboration and adaptation to user needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional software agents use complex knowledge models to operate autonomously, then agent functionality and autonomy are improved, but development cost and system complexity increase significantly
Solution Approach 1:
The patent introduces a semantic network as an intermediary layer between users and agents. Instead of requiring complex knowledge models within agents, the semantic network serves as a shared knowledge base that mediates interactions. Users can modify the semantic network directly, and agents automatically adapt their behavior based on changes in this intermediary structure, thereby reducing agent complexity while maintaining autonomy.
Solution Approach 2:
The semantic network serves multiple functions simultaneously: it stores knowledge, enables user customization, facilitates agent communication, and provides a foundation for autonomous decision-making. This multi-functional approach eliminates the need for separate complex knowledge models in each agent, as the universal semantic network serves all agents' needs.
2Adaptability or versatility
If agents are designed to adapt to changing user needs, then adaptability is improved, but the cost and difficulty of updating and maintaining agents increases
Solution Approach 1:
The semantic network is designed to be dynamic and easily modifiable. Users can update the network structure, add new concepts, or modify relationships without requiring agent reconfiguration. This dynamic nature allows the system to adapt to changing user needs while keeping maintenance simple, as changes are made at the high-level semantic network rather than within individual agents.
Solution Approach 2:
The system separates the knowledge representation (semantic network) from the agent logic. This segmentation allows the knowledge base to be independently updated and maintained without affecting agent functionality. Users can modify the semantic network to reflect changing needs, and agents automatically pick up these changes without requiring manual updates to their core logic.
3Productivity
If multiple agents interact autonomously in a distributed system, then system functionality is improved, but coordination complexity and communication overhead increase
Solution Approach 1:
The patent merges the knowledge representations of multiple agents into a single unified semantic network. Instead of requiring complex inter-agent communication protocols to coordinate, all agents access and interact with the same shared knowledge base. This merging simplifies coordination by providing a common reference framework, while still enabling rich collaborative functionality through the network.
Data Source
AI summary
A system, method and computer program product in which semi-autonomous agents interact with a semantic network. In a basic embodiment of the system, a data structure providing a semantic network is provided in a non-transitory, computer-readable medium within a computer network. A plurality of computer-implemented agents are deployed within the computer network and interactive with the semantic network. A user interface is provided and configured to permit a user to create and/or modify the semantic network. The agents are configured to read and modify the semantic network without receiving explicit instructions from a user after their initial deployment, whereby the agents operate as assistants to support the user's use of the network.