Learning Contextual Runtime Monitors for Safe AI-Based Autonomy

Overview

This framework learns context-aware monitors that select suitable ML controllers instead of averaging their outputs. Contextual-bandit techniques support controller diversity, with theoretical safety conditions and evaluations in simulated autonomous-driving scenarios.