Jonathan P. How

Jonathan P. How

Massachusetts Institute of Technology

Professor

Department of Aeronautics and Astronautics

Research Area

  • #Computer science
  • #Artificial intelligence
  • #Engineering
  • #Control system
  • #Robot
  • #Engineering ethics
  • #Machine learning
  • #Algorithm
  • #Gaussian process
  • #Reinforcement learning

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Related papers to
‘ Computer science ‘ : 54

  • Bayesian Nonparametric Reward Learning From Demonstration

    2015/04

    2.0 Impact Factor

    56 citations

    Bernard Michini, Thomas J. Walsh, Ali-Akbar Agha-Mohammadi, Jonathan P. How

    DOI : 10.1109/TRO.2015.2405593

    • #Computer science
    • #Artificial intelligence
    • #Machine learning
    • #Robot
    • #Trajectory
    • #Approximation algorithm
    • #Autonomous system (Internet)
    • #Unsupervised learning
    • #Gaussian process
    • #Bayesian nonparametrics
    • #Reward learning

All papers authored by
‘ Jonathan P. How ’ : 95

  • Bayesian Nonparametric Adaptive Control Using Gaussian Processes

    2015/03
    IEEE TRANSACTIONS ON NEURAL NETWORKS

    2.8 Impact Factor

    117 citations

    Girish Chowdhary, Hassan A. Kingravi, Jonathan P. How, Patricio A. Vela

    DOI : 10.1109/TNNLS.2014.2319052

    • #Mathematics
    • #Artificial intelligence
    • #Algorithm
    • #Machine learning
    • #Control theory
    • #Parametric statistics
    • #Bayesian probability
    • #Kernel (linear algebra)
    • #A priori and a posteriori
    • #Domain knowledge
    • #Adaptive control
    • #Gaussian process

Related papers to
‘ Computer science ‘ : 54

  • Bayesian Nonparametric Reward Learning From Demonstration

    2015/04
    IEEE TRANSACTIONS ON ROBOTICS

    2.0 Impact Factor

    56 citations

    Bernard Michini, Thomas J. Walsh, Ali-Akbar Agha-Mohammadi, Jonathan P. How

    DOI : 10.1109/TRO.2015.2405593

    • #Computer science
    • #Artificial intelligence
    • #Machine learning
    • #Robot
    • #Trajectory
    • #Approximation algorithm
    • #Autonomous system (Internet)
    • #Unsupervised learning
    • #Gaussian process
    • #Bayesian nonparametrics
    • #Reward learning
  • RLPy: a value-function-based reinforcement learning framework for education and research

    2015/01
    JOURNAL OF MACHINE LEARNING RESEARCH

    2.5 Impact Factor

    33 citations

    Alborz Geramifard, Christoph Dann, Robert H. Klein, William Dabney, Jonathan P. How

    • #Computer science
    • #Artificial intelligence
    • #Machine learning
    • #Programming language
    • #Reinforcement learning
    • #License
    • #Profiling (computer programming)
    • #Open source
    • #Python (programming language)
    • #Linear function
    • #Bellman equation
    • #Software package

Get access to
Contact information

Log in

All papers authored by
‘ Jonathan P. How ’ : 95

  • Bayesian Nonparametric Adaptive Control Using Gaussian Processes

    2015/03
    IEEE TRANSACTIONS ON NEURAL NETWORKS

    2.8 Impact Factor

    117 citations

    Girish Chowdhary, Hassan A. Kingravi, Jonathan P. How, Patricio A. Vela

    DOI : 10.1109/TNNLS.2014.2319052

    • #Mathematics
    • #Artificial intelligence
    • #Algorithm
    • #Machine learning
    • #Control theory
    • #Parametric statistics
    • #Bayesian probability
    • #Kernel (linear algebra)
    • #A priori and a posteriori
    • #Domain knowledge
    • #Adaptive control
    • #Gaussian process
  • An Automated Battery Management System to Enable Persistent Missions With Multiple Aerial Vehicles

    2015/02
    IEEE-ASME TRANSACTIONS ON MECHATRONICS

    3.9 Impact Factor

    95 citations

    N. Kemal Ure, Girish Chowdhary, Tuna Toksoz, Jonathan P. How, Matthew A. Vavrina, John Vian

    DOI : 10.1109/TMECH.2013.2294805

    • #Engineering
    • #Automotive engineering
    • #Real-time computing
    • #Probabilistic logic
    • #Markov process
    • #Algorithm design
    • #Multi-agent system
    • #Mechatronics
    • #Downtime
    • #Flight test
    • #Battery (electricity)

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