A Local Agentic AI Framework to Generate Edge Case Scenarios for Safety Assurance
Generating edge case scenarios is crucial for training, testing and safety assuring autonomous systems.
ProofPaper ↗
Key points
- The rapid advancement in the generation and analysis capabilities of language models (LMs) has expanded their applicability and recent work has investigated LM scenario generation.
- Our work uses local LMs in a laptop-based agentic AI framework for adaptive scenario generation.
- We use the system requirements, system description and environment description as knowledge bases in contextual prompts for an LM to ensure scenario realism.
- Our work highlights the potential of a flexible and adaptive local agentic AI framework for automating edge case generation and producing traceable safety assurance evidence.
Sources (1)
- [1]A Local Agentic AI Framework to Generate Edge Case Scenarios for Safety AssurancearXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 9, 12:13 PM
Generating edge case scenarios is crucial for training, testing and safety assuring autonomous systems.
The rapid advancement in the generation and analysis capabilities of language models (LMs) has expanded their applicability and recent work has investigated LM scenario generation.
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