Search for dissertations about: "policy iteration"
Showing result 6 - 10 of 10 swedish dissertations containing the words policy iteration.
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6. Practice beyond technology when programming and mathematics teaching converge
Abstract : This thesis examines how computer programming and mathematics teaching converge in the presence of a revised mathematics curriculum for upper secondary education. The focus is on the stratified policy strategies deployed by the institutions; how teachers tactically navigated the tensions and contradictions that arose in their everyday teaching; and how these tactics later consolidated in practice. READ MORE
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7. Approximate Methods of Optimal Control via Dynamic Programming Models
Abstract : Optimal control theory has a long history and broad applications. Motivated by the goal of obtaining insights through unification and taking advantage of the abundant capability to generate data and perform online simulation, this thesis studies the discrete-time infinite horizon optimal control problems and introduces some approximate solution methods via abstract dynamic programming (DP) models. READ MORE
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8. Structure exploiting optimization methods for model predictive control
Abstract : This thesis considers optimization methods for Model Predictive Control (MPC). MPC is the preferred control technique in a growing set of applications due to its flexibility and to the natural way in which constraints can be incorporated in the control policy. READ MORE
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9. Sharing Good Examples, Then What? : Investigations of Contingency and Continuity in the Scaling-of-ESD-Activities-as-Learning
Abstract : This thesis aims to contribute to a deepened and nuanced understanding of scaling in environmental and sustainability education (ESE) research, specifically, to develop a conceptual framework for engaging with issues of scaling in policy and practice regarding education for sustainable development (ESD). Three research objectives are formulated. READ MORE
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10. Reinforcement Learning and Dynamical Systems
Abstract : This thesis concerns reinforcement learning and dynamical systems in finite discrete problem domains. Artificial intelligence studies through reinforcement learning involves developing models and algorithms for scenarios when there is an agent that is interacting with an environment. READ MORE