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Cognition Envelopes for Bounded Decision Making in Autonomous UAS Operations
arXiv – CS AI|Pedro Antonio Alarcon Granadeno, Arturo Miguel Bernal Russell, Sofia Nelson, Demetrius Hernandez, Maureen Petterson, Michael Murphy, Walter J. Scheirer, Jane Cleland-Huang|
🤖AI Summary
Researchers introduce 'Cognition Envelopes' as a new framework to constrain AI decision-making in autonomous systems, addressing errors like hallucinations in Large Language Models and Vision-Language Models. The approach is demonstrated through autonomous drone search and rescue missions, establishing reasoning boundaries to complement traditional safety measures.
Key Takeaways
- →Cognition Envelopes are proposed as a new method to establish reasoning boundaries that constrain AI-generated decisions in autonomous systems.
- →The framework addresses critical AI model errors including hallucinations, over-generalizations, and context misalignments.
- →Researchers demonstrated the approach using LLM/VLM-supported pipelines for autonomous drone search and rescue operations.
- →The methodology combines probabilistic reasoning and resource analysis to validate AI decisions in cyber-physical systems.
- →Key software engineering challenges remain for systematically designing and validating Cognition Envelopes in real-world deployments.
#ai-safety#autonomous-systems#llm#vlm#cyber-physical#drone-technology#search-rescue#ai-governance#machine-learning#robotics
Read Original →via arXiv – CS AI
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