{"id":"W2618318883","doi":"10.48550/arxiv.1705.08551","title":"Safe Model-based Reinforcement Learning with Stability Guarantees","year":2017,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":337,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Reinforcement learning; Inverted pendulum; Stability (learning theory); Computer science; State space; Artificial neural network; Lyapunov function; Gaussian process; Process (computing); State (computer science); Artificial intelligence; Control (management); Control theory (sociology); Machine learning; Gaussian; Algorithm; Mathematics; Nonlinear system","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0607400630856931,"score_gpt":0.1995221572087716,"score_spread":0.1387820941230785,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}