Safe Exploration
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AI Safety Gridworlds
• deepmind/ai-safety-gridworlds
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We present a suite of reinforcement learning environments illustrating various safety properties of intelligent agents.
Learning-based Model Predictive Control for Safe Exploration
However, these methods typically do not provide any safety guarantees, which prevents their use in safety-critical, real-world applications.
Safe Exploration in Finite Markov Decision Processes with Gaussian Processes
NeurIPS 2016 • befelix/SafeMDP
We define safety in terms of an, a priori unknown, safety constraint that depends on states and actions.
Concrete Problems in AI Safety
• mateuszjurewicz/bornhack_ml_crashcourse
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Rapid progress in machine learning and artificial intelligence (AI) has brought increasing attention to the potential impacts of AI technologies on society.
Safe Exploration in Continuous Action Spaces
We address the problem of deploying a reinforcement learning (RL) agent on a physical system such as a datacenter cooling unit or robot, where critical constraints must never be violated.