Litcius/Paper detail

Reinforcement learning and approximate Bayesian computation for model selection and parameter calibration applied to a nonlinear dynamical system

Thiago Ritto, Sándor Beregi, David A. W. Barton

2022Mechanical Systems and Signal Processing16 citationsDOIOpen Access PDF

Topics & Concepts

Approximate Bayesian computationModel selectionReinforcement learningNonlinear systemComputer scienceComputationContext (archaeology)Artificial intelligencePosterior probabilityMachine learningBayesian inferenceBayesian probabilityCalibrationSelection (genetic algorithm)AlgorithmMathematicsStatisticsInferenceBiologyPaleontologyQuantum mechanicsPhysicsModel Reduction and Neural NetworksProbabilistic and Robust Engineering DesignProtein Structure and Dynamics
Reinforcement learning and approximate Bayesian computation for model selection and parameter calibration applied to a nonlinear dynamical system | Litcius