Agent Evaluation Metrics are a structured set of quantitative and qualitative measurements used to assess the performance, reliability, safety, and effectiveness of agentic AI systems.
An agent executor is a specialized component or role within an agentic AI system responsible for carrying out concrete actions determined by a reasoning or planning process.
Agent Failure Recovery refers to the set of mechanisms and processes that enable an agentic AI system to detect failures, respond safely, restore functionality, and resume operation with minimal disruption.
Agent Lifecycle Management is the structured process of designing, deploying, operating, monitoring, updating, and retiring agentic AI systems throughout their operational lifecycles.
Agent negotiation is the structured process by which autonomous or semi-autonomous AI agents communicate, evaluate options, and reach agreements when their goals, constraints, resources, or preferences differ.
