Evaluating Long-Term Behavior in Autonomous AI Agents
Anchor Research studies how AI agents behave over extended periods—days or weeks at a time. We detect problems like goal drift, unsafe failures, and risky adaptations before they become critical.
Why Long-Term Evaluation Matters
Current AI safety checks often measure short-term tasks. But if an agent runs continuously for a week, will it still follow its intended instructions on day seven as it did on day one?
Goal Drift
Agents gradually shifting away from their original objectives over time.
Unsafe Failures
Getting stuck in dangerous cycles that fail to progress safely.
Risky Adaptations
Adopting new strategies that might be unsafe or misaligned.
Early Detection
Catching these issues before they become critical or dangerous.
Our Approach
Evaluation Frameworks
We design methods to observe agent behavior across different time scales, from hours to weeks.
Open-Source Tools
Building prototypes like our long_agent_framework to help others run extended tests.
Collaboration
Working with AI labs and research groups for deeper insights into long-run stability.
Current Projects
- AISI Bounty Programme contribution
- CHAI collaboration
- Long-term agent framework development
Get Involved
We're keen to collaborate with AI labs, researchers, and policy entities who want to understand long-term agent behavior.