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  1. ieeexplore.ieee.org

    Cost functions have the potential to provide compact and understandable generalizations of motion. The goal of inverse optimal control (IOC) is to analyze an observed behavior which is assumed to be optimal with respect to an unknown cost function, and infer this cost function. Here we develop a method for characterizing cost functions of legged locomotion, with the goal of representing ...
    Author:John R. Rebula, Stefan Schaal, James Finley, Ludovic RighettiPublished:2019
  2. A Robustness Analysis of Inverse Optimal Control of Bipedal Walking John R. Rebula1, Stefan Schaal2, James Finley3, Ludovic Righetti1;4 Abstract—Cost functions have the potential to provide com-pact and understandable generalizations of motion. The goal of Inverse Optimal Control (IOC) is to analyze an observed behav-
    Author:John R. Rebula, Stefan Schaal, James Finley, Ludovic RighettiPublished:2021
  3. semanticscholar.org

    The goal of inverse optimal control (IOC) is to analyze an observed behavior which is assumed to be optimal with respect to an unknown cost function, and infer this cost function. Here we develop a method for characterizing cost functions of legged locomotion, with the goal of representing complex humanoid behavior with simple models.
  4. researchgate.net

    Inverse optimal control, also known as inverse reinforcement learning, is the problem of recovering an unknown reward function in a Markov decision process from expert demonstrations of the ...
  5. publikationen.uni-tuebingen.de

    A Robustness Analysis of Inverse Optimal Control of Bipedal Walking DSpace Repositorium (Manakin basiert) ... A Robustness Analysis of Inverse Optimal Control of Bipedal Walking; Autor(en): Rebula, John R.; Schaal, Stefan; Finley, James; Righetti, Ludovic: Tübinger Autor(en):
  6. catalyzex.com

    A Robustness Analysis of Inverse Optimal Control of Bipedal Walking. Click To Get Model/Code. Cost functions have the potential to provide compact and understandable generalizations of motion. The goal of Inverse Optimal Control (IOC) is to analyze an observed behavior which is assumed to be optimal with respect to an unknown cost function, and infer this cost function.
  7. Cost functions have the potential to provide compact and understandable generalizations of motion. The goal of Inverse Optimal Control (IOC) is to analyze an observed behavior which is assumed to be optimal with respect to an unknown cost function, and infer this cost function. Here we develop a method for characterizing cost functions of legged locomotion, with the goal of representing ...
  8. cs.reviewer.ly

    A Robustness Analysis of Inverse Optimal Control of Bipedal Walking. John R. Rebula Stefan Schaal James M. Finley Ludovic Righetti. Published in: IEEE Robotics Autom. Lett. (2019) Keyphrases </> optimal control; neural network; control problems; dynamic programming; machine learning; steady state;

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