Search for dissertations about: "Bayesian Reinforcement Learning"

Showing result 1 - 5 of 13 swedish dissertations containing the words Bayesian Reinforcement Learning.

  2. 1. Sample Efficient Bayesian Reinforcement Learning

    Author : Divya Grover; Chalmers tekniska högskola; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Decision Making under Uncertainty; Bayesian Reinforcement Learning; Model based Reinforcement Learning;

    Abstract : Artificial Intelligence (AI) has been an active field of research for over a century now. The research field of AI may be grouped into various tasks that are expected from an intelligent agent; two major ones being learning & inference and planning . READ MORE

  4. 2. Reinforcement Learning and Dynamical Systems

    Author : Björn Lindenberg; Karl-Olof Lindahl; Marc G. Bellemare; Linnéuniversitetet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; artificial intelligence; distributional reinforcement learning; Markov decision processes; Bellman operators; deep learning; multi-armed bandits; Bayesian bandits; conjugate priors; Thompson sampling; linear finite dynamical systems; cycle orbits; fixed-point systems; Mathematics; Matematik; Computer Science; Datavetenskap;

    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

  5. 3. Priors and uncertainty in reinforcement learning

    Author : Emilio Jorge; Chalmers tekniska högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Bayesian reinforcement learning; reinforcement learning; Minimax; Markov decision processes;

    Abstract : Handling uncertainty is an important part of decision-making. Leveraging uncertainty for guiding exploration to discover higher rewards has been a standard approach for a long time, using both ad hoc and more principled approaches. READ MORE

  6. 4. Computational Modeling of the Basal Ganglia : Functional Pathways and Reinforcement Learning

    Author : Pierre Berthet; Anders Lansner; Kenji Doya; Stockholms universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; computational neuroscience; modelisation; reinforcement learning; basal ganglia; dopamine; datalogi; Computer Science;

    Abstract : We perceive the environment via sensor arrays and interact with it through motor outputs. The work of this thesis concerns how the brain selects actions given the information about the perceived state of the world and how it learns and adapts these selections to changes in this environment. READ MORE

  7. 5. Spike-Based Bayesian-Hebbian Learning in Cortical and Subcortical Microcircuits

    Author : Philip Tully; Anders Lansner; Matthias Hennig; Gordon Pipa; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Bayes rule; synaptic plasticity and memory modeling; intrinsic excitability; naïve Bayes classifier; spiking neural networks; Hebbian learning; neuromorphic engineering; reinforcement learning; temporal sequence learning; attractor network; Computer Science; Datalogi;

    Abstract : Cortical and subcortical microcircuits are continuously modified throughout life. Despite ongoing changes these networks stubbornly maintain their functions, which persist although destabilizing synaptic and nonsynaptic mechanisms should ostensibly propel them towards runaway excitation or quiescence. READ MORE