Third-party cyber evaluations involving OpenAI models
openai.com·13h ago
AI Research
arXiv CS.AI·Jun 9·5 min read
Engagement Process: Rethinking the Temporal Interface of Action and Observation
TL;DR
Task completion often involves complex interactions where actions and observations do not align with fixed steps. The Engagement Process (EP) is introduced as a new framework that explicitly models these interactions by decoupling actions and observations.
✦ Why It Matters
Engineers can leverage the Engagement Process to improve decision-making models in complex, time-sensitive environments.
Key Takeaways
- Implement EP to model actions and observations as separate streams.
- Utilize EP to address timing issues in AI interactions.
- Explore EP's potential in both digital and physical environments.
- Adapt policies based on explicit time costs for better performance.
How It Works
EP operates by decoupling actions and observations into distinct event streams, allowing for a more nuanced understanding of timing in decision-making. This structure enables agents to manage delays and feedback more effectively, leading to improved coordination and interaction among subsystems.