AWS Machine Learning Blog· Kanishk Mahajan·· 11 d ago
Evaluating multi-agent systems for explainability and helpfulness with Amazon Bedrock AgentCore
Evaluating multi-agent systems for explainability and helpfulness with Amazon Bedrock AgentCore
AI summary
Multi-agent systems need deeper guarantees than fluent responses: they must select the right tools, respect constraints, and explain their decisions. Learn how to build a Strands-based multi-agent supply chain decisioning system and evaluate it with Amazon Bedrock AgentCore Evaluations using built-in, custom, and explainability evaluators.
Selection record
Threshold 60Official, first-handFirst 34Second 38
Not admittedSum of both 72 < twice the threshold 120
- Source tier
- Official, first-hand; this tier's threshold is 60
- Pre-filter
- passed：多智能体系统评测与AgentCore平台技术文章
A model scores each item twice, independently, against one written standard, out of 100. An item is admitted only when the two scores add up to twice the threshold. The threshold is set per source tier.
Source: AWS Machine Learning Blog · aws.amazon.com