Agent Module Trust Score Calculation via Capability Intention Policy Segmentation
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Solution Overview
Problem
In multi-agent systems, existing trust and reputation mechanisms are insufficiently accurate in determining the reliability and capability of agents, particularly in complex environments where agents share resources and interact with varying levels of trustworthiness.
Innovation Solution
A method and communication device that calculate a score for an agent module based on its capability, intention, and policy, considering factors like time, space, and hardware usage, to improve the accuracy of trust assessments between agents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing trust and reputation mechanisms are used to assess agent reliability, then the system can operate with simple assessment methods, but the accuracy of trust determination is insufficient
Solution Approach 1:
The patent segments the trust assessment into multiple independent dimensions: capability (what the agent can do), intention (what the agent wants to do), and policy (how the agent should behave). Each dimension is assessed separately using specific criteria, allowing for comprehensive evaluation without requiring a single complex assessment mechanism. This segmentation enables accurate determination of agent reliability by evaluating each aspect independently and combining the results.
2Measurement precision
If comprehensive information about agent capability, intention, and policy is collected, then the accuracy of trust assessment improves, but the complexity of data processing increases
Solution Approach 1:
The patent applies local quality by assigning different assessment criteria and weights to different aspects of agent evaluation. Each dimension (capability, intention, policy) has its own specific evaluation criteria tailored to that aspect. For example, capability assessment focuses on technical abilities and resource availability, while policy assessment focuses on behavioral rules and constraints. This localized approach to each assessment area improves overall accuracy without requiring a monolithic complex processing system.
Solution Approach 2:
The patent introduces multiple assessment dimensions (capability, intention, policy) to evaluate agents, transforming a single-dimensional trust score into a multi-dimensional evaluation framework. Each dimension provides a different perspective on agent reliability, and the combination of these dimensions creates a more nuanced and accurate assessment. This dimensional approach allows the system to capture the complexity of agent behavior without requiring excessively complex processing, as each dimension can be evaluated independently.
3Adaptability or versatility
If simple trust mechanisms are used in multi-agent systems, then the system operation is easier, but the ability to handle complex interactions and resource sharing is insufficient
Solution Approach 1:
The patent creates a universal assessment framework that can evaluate agents across multiple functions and interaction types. The same three-dimensional structure (capability, intention, policy) is applied regardless of the specific interaction scenario, whether it involves resource sharing, task collaboration, or data exchange. This universal approach enables the system to handle complex interactions adaptively while maintaining ease of operation, as the assessment mechanism remains consistent across different contexts and does not require separate mechanisms for each interaction type.
Data Source
AI summary
A method and a communication device for determining a score relating to a first agent module are described. The communication device receives information relating to at least one request, performed by another agent module separate from the first agent module, for consumption of a capability of the first agent module. The information relating to the at least one request includes information about the capability of the first agent module, information about an intention of the first agent module, and information about a policy for the capability. The communication device calculates the score in relation to the first agent module based on the information relating to the at least one request, wherein the score further is specified with respect to the capability.