ENPIRE: Agentic Robot Policy Self-Improvement in the Real World
Achieving dexterous robotic manipulation in the real world heavily relies on human supervision and algorithm engineering, which becomes a central bottleneck in the pursuit of general physical intelligence. Although emerging coding agents can generate code to automate algorithm search, their successes remain largely confined in digital environments. We conjecture that the missing abstraction to automate robotics research is a repeatable feedback loop for real-world policy improvement: reset the s
Record details
Published: 18 June 2026
Source: arXiv
Category: Research
Topics: Regulation · Agents & autonomy · Environment
Retrieved: 14 July 2026
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ethics.ai (18 June 2026), “ENPIRE: Agentic Robot Policy Self-Improvement in the Real World,” evidence record 812, https://ethics.ai/record/812 (originally published by arXiv).
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