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Showing 1 to 2 of 2 for “"Parametric Q-learning"”.

  1. Modifications of Q-learning to Optimize Dynamic Treatment Regimes

    … DTR for an individual subject, among which Q-learning with linear regression is widely used due to its simplicity and ease of interpretation. This thesis discusses three important challenges that cause problems in the implementation of Q-learning and proposes multiple modifications of …

    umn Repository record for Modifications of Q-learning to Optimize Dynamic Treatment Regimes (opens in a new tab)

  2. Value function approximation architectures for neuro-dynamic programming

    … errors. Next, we propose a novel parameterized Q-learning algorithm. Q-learning is a model-free method to compute the Q-function associated with an optimal policy, based on observations of states and actions. If the size of a state or a policy space is too large, Q-learning is often not very …

    uiuc Repository record for Value function approximation architectures for neuro-dynamic programming (opens in a new tab)