Publications

    Reinforcement Learning

  • J. Eastep, D. Wingate, M. D. Santambrogio, A. Agarwal:
    Smartlocks: Lock Acquisition Scheduling for Self-Aware Synchronization (pdf) (bibtex)
    IEEE International Conference on Autonomic Computing and Communications
    #mutex, #reinforcement learning, #adaptive
    @article{J.Eastep:2010:75b1e,
    author = {J. Eastep and D. Wingate and M. D. Santambrogio and A. Agarwal},
    journal = {IEEE International Conference on Autonomic Computing and Communications},
    title = {Smartlocks: Lock Acquisition Scheduling for Self-Aware Synchronization },
    year = {2010},
    keywords = {mutex, reinforcement learning, adaptive},
    doi = {},
    url = {http://web.mit.edu/~wingated/www/papers/icac10.pdf}
    }
  • J. Asmuth, L. Li, M. L. Littman, A. Nouri and D. Wingate:
    A Bayesian Sampling Approach to Exploration in Reinforcement Learning (pdf) (bibtex)
    Uncertainty in Artificial Intelligence
    #bayesian, #sampling, #reinforcement learning
    @article{J.Asmuth:2009:0134d,
    author = {J. Asmuth and L. Li and M. L. Littman and A. Nouri and D. Wingate},
    journal = {Uncertainty in Artificial Intelligence},
    title = {A Bayesian Sampling Approach to Exploration in Reinforcement Learning },
    year = {2009},
    keywords = {bayesian, sampling, reinforcement learning},
    doi = {},
    url = {http://web.mit.edu/~wingated/www/papers/boss.pdf}
    }
  • D. Wingate, C. Diuk, T. O’Donnell, J.B. Tenenbaum, S.J. Gershman:
    Compositional policy priors (pdf) (bibtex)
    MIT CSAIL Technical Report 2013-007
    #reinforcement learning, #grammar induction
    @article{D.Wingate:2013:8a8cd,
    author = {D. Wingate and C. Diuk and T. O’Donnell and J.B. Tenenbaum and S.J. Gershman},
    journal = {MIT CSAIL Technical Report 2013-007},
    title = {Compositional policy priors},
    year = {2013},
    keywords = {reinforcement learning, grammar induction},
    doi = {},
    url = {http://web.mit.edu/sjgershm/www/MIT-CSAIL-TR-2013-007.pdf}
    }
  • S.J. Gershman, E.J. Horvitz, J.B. Tenenbaum:
    Computational rationality: a converging paradigm for intelligence in brains, minds, and machines (pdf) (bibtex)
    Science
    #decision making, #reinforcement learning, #hypothesis sampling
    @article{S.J.Gershman:2015:79191,
    author = {S.J. Gershman and E.J. Horvitz and J.B. Tenenbaum},
    journal = {Science},
    title = {Computational rationality: a converging paradigm for intelligence in brains, minds, and machines},
    year = {2015},
    keywords = {decision making, reinforcement learning, hypothesis sampling},
    doi = {},
    url = {http://web.mit.edu/sjgershm/www/GershmanHorvitzTenenbaum15.pdf}
    }
  • Tejas D Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Josh Tenenbaum:
    Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation (web) (bibtex)
    Advances in Neural Information Processing Systems (NIPS)
    #reinforcement learning, #hierarchical modeling, #deep learning
    @article{TejasDKulkarni:2016:847fe,
    author = {Tejas D Kulkarni and Karthik Narasimhan and Ardavan Saeedi and Josh Tenenbaum},
    journal = {Advances in Neural Information Processing Systems (NIPS)},
    title = {Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation},
    year = {2016},
    keywords = {reinforcement learning, hierarchical modeling, deep learning},
    doi = {},
    url = {http://papers.nips.cc/paper/6232-hierarchical-deep-reinforcement-learning-integrating-temporal-abstraction-and-intrinsic-motivation}
    }

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