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Showing 1 to 9 of 9 for “"Apprenticeship Learning"”.

  1. Faster apprenticeship learning through inverse optimal control

    … problems of artificial intelligence is learning how to behave optimally. With applications ranging from self-driving cars to medical devices, this task is vital to modern society. There are two complementary problems in this area – reinforcement learning and inverse reinforcement …

    uiuc Repository record for Faster apprenticeship learning through inverse optimal control (opens in a new tab)

  2. A Mixed Methods Study of On-Farm Apprenticeship Learning in Virginia

    … effectively preparing beginning farmers. On-farm apprenticeships in the U.S. show promise as a means to prepare farmers and are increasing in number (Niewolny and Lillard, 2010). Lave (1988) writes 'knowledge-in-practice, constituted in the settings of practice, is the locus of the most powerful …

    vt Repository record for A Mixed Methods Study of On-Farm Apprenticeship Learning in Virginia (opens in a new tab)

  3. System Design Framework for a Learning Collaboratory

    … More recent work has focused on collaborative learning processes, and the idea of a collaboratory as a virtual space for work. This thesis describes a design process to support the development and use of collaborative learning technologies. This process, the Learning Collaboratory Design …

    uiuc Repository record for System Design Framework for a Learning Collaboratory (opens in a new tab)

  4. Knowledge and Ignorance in Reinforcement Learning

    The field of Reinforcement Learning is concerned with teaching agents to take optimal decisions to maximize their total utility in complicated environments. A Reinforcement Learning problem, generally described by the Markov Decision Process formalism, has several complex interacting components, …

    uiuc Repository record for Knowledge and Ignorance in Reinforcement Learning (opens in a new tab)

  5. From cognitive to docitive radios: the role of machine learning in intelligent wireless multimedia networks

    … networking techniques and cutting-edge machine learning techniques. Particularly, crosslayer design for multimedia transmission, spectrum handoff for cognitive radio networks, and multichannel wireless mesh networks with multi-beam antennas are addressed for the improvement of multimedia …

    alabama Repository record for From cognitive to docitive radios: the role of machine learning in intelligent wireless multimedia networks (opens in a new tab)

  6. Enabling young composers through the Vermont MIDI Project: Composition, verbalization and communication

    … mentoring project is an example of the cognitive apprenticeship learning paradigm (Collins et al., 1989). The apparent technological limitations on communication in online mentoring afford unique pedagogical benefits for all the participants, including students, teachers, and mentors. In …

    uiuc Repository record for Enabling young composers through the Vermont MIDI Project: Composition, verbalization and communication (opens in a new tab)

  7. Modeling users' powertrain preferences

    … determine the driver's preferences. A supervised learning approach has already been applied to this problem. However, because the approach locally classify a small interval at a time and is memoryless, the supervised learning does not perform well on our goal. Instead, we need to introduce new …

    mit Repository record for Modeling users' powertrain preferences (opens in a new tab)

  8. Human-machine collaborative optimization via apprenticeship scheduling

    … I believe robots must be capable of autonomously learning from humans how to integrate into a team ' la a human apprentice. Human domain experts and professionals become experts over years of apprenticeship, and this knowledge is not easily codified in the form of a policy. In my thesis, I develop …

    mit Repository record for Human-machine collaborative optimization via apprenticeship scheduling (opens in a new tab)

  9. Inverse optimal control for deterministic continuous-time nonlinear systems

    … optimal control to develop a new method of learning from demonstration for quadrotor dynamic maneuvering. We compare and contrast our method with an existing state-of-the-art solution based on minimum-time optimal control, and show that our method can generalize to novel tasks and reject …

    uiuc Repository record for Inverse optimal control for deterministic continuous-time nonlinear systems (opens in a new tab)