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Filtering by: Creator Gilbert, Erin H. Remove constraint Creator: Gilbert, Erin H. Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad Decade 2020-2029 Remove constraint Decade: 2020-2029

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  • Learning and Improving Policies for Probabilistic Planning Problems

    Creator:
    Issakkimuthu, Murugeswari
    Abstract:
    In this work, we study the problem of learning and improving policies for probabilistic planning problems. In the first part, we train neural network policies for probabilistic planning problems modeled as factored Markov decision problems. The objective is to train problem-specific neural networks via supervised learning to imitate the action...
    Resource Type:
    Dissertation
    Full Text:
    online lectures of Prof. Dimitri Bertsekas and Prof. Gilbert Strang at MIT. I would like to thank them

  • Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

    Creator:
    Dodge, Jonathan E.
    Abstract:
    Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...
    Resource Type:
    Dissertation
    Full Text:
    manipulate the agent “quality”? . . . . . . . . . . . . . . . . . . . . 165 H The Heuristic Agent

  • Improving and Understanding Deep Models for Natural Language Comprehension

    Creator:
    Ghaeini, Reza
    Abstract:
    Natural Language Comprehension is a challenging domain of Natural Language Processing. To improve a model’s language comprehension/understanding, one approach would be to enrich the structure of the model to enhance its capability in learning the latent rules of the language. In this dissertation, we will first introduce several deep models...
    Resource Type:
    Dissertation
    Full Text:
    embedding that performs appropriately in all 10 h y x y1 x1 y2 x2 y3 x3 yn xn Unfold Figure