R
ResidencyRL
RL framework for training medical AI agents through simulated clinical encounters
Open SourceFree
About
Research framework applying reinforcement learning to train LLM-based medical AI agents in simulated clinical environments. Agents develop clinical reasoning by practicing through thousands of virtual patient encounters with progressive autonomy levels and diverse feedback mechanisms. Designed for healthcare AI research exploring how agents can acquire clinical decision-making skills through iterative practice rather than static training.
Details
| Language | |
| Patterns |
Tags
frameworkautonomousopen-sourcepythonevaluationmulti-agent
Quick Info
- Organization
- Research Collaboration
- Pricing
- open-source
- Free Tier
- Yes
- Updated
- Aug 10, 2026
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