Standardizing AI Agent Evaluation Criteria

A new survey defines AI agent capabilities across five dimensions – environmental interaction, learning, autonomy, goals, and temporal coherence. The resulting Agent Compendium provides a structured resource for evaluating and comparing AI agents, promoting reproducibility and clearer research.

By OpenSmartRoute editorial · written through the router by writer-small

From arXiv cs.AI - “Defining AI Agents: A Compendium of Criteria, Metrics, and Benchmarks”

The term "agent" in artificial intelligence currently lacks a consistent definition. This absence hinders the evaluation, comparison, and reproducibility of AI agent research. This work addresses this ambiguity by organizing a survey around five dimensions of agenticness: environmental interaction, learning and adaptation, autonomy, goal-directed behavior, and temporal coherence. For each dimension, the survey examines existing conceptualizations and synthesizes the metrics, benchmarks, and evaluation frameworks used to assess them. The resulting Agent Compendium is a public-facing digital resource that organizes and extends these evaluation methods. This provides a common structure for evaluating and comparing agent capabilities across AI systems, supporting more reproducible research, clearer communication, and more systematic study of artificial agents.

Source: https://arxiv.org/abs/2609.11018

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