Essays about: "djup förstärkningsinlärning"
Showing result 11 - 15 of 26 essays containing the words djup förstärkningsinlärning.
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11. Reinforcement Learning for Market Making
University essay from KTH/Matematisk statistikAbstract : Market making – the process of simultaneously and continuously providing buy and sell prices in a financial asset – is rather complicated to optimize. Applying reinforcement learning (RL) to infer optimal market making strategies is a relatively uncharted and novel research area. READ MORE
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12. Spiking Reinforcement Learning for Robust Robot Control Under Varying Operating Conditions
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Over the last few years, deep reinforcement learning (RL) has gained increasing popularity for its successful application to a variety of complex control and decision-making tasks. As the demand for deep RL algorithms deployed in challenging real-world environments grows, their robustness towards uncertainty, disturbances and perturbations of the environment becomes more and more important. READ MORE
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13. Modelling Financial Markets via Multi-Agent Reinforcement Learning : How nothing interesting happened when I made AI trade with AI
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The numerous previous attempts to simulate financial markets tended to be based on strong assumptions about markets or their participants. This thesis describes a more general kind of model - one in which deep reinforcement learning is used to train agents to make a profit while trading with each other on a virtual exchange. READ MORE
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14. Benchmarking Deep Reinforcement Learning on Continuous Control Tasks : AComparison of Neural Network Architectures and Environment Designs
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Deep Reinforcement Learning (RL) has received much attention in recent years. This thesis investigates how reward functions, environment termination conditions, Neural Network (NN) architectures, and the type of the deep RL algorithm aect the performance for continuous control tasks. READ MORE
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15. Deep Reinforcement Learning for Building Control : A comparative study for applying Deep Reinforcement Learning to Building Energy Management
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Energy and environment have become hot topics in the world. The building sector accounts for a high proportion of energy consumption, with over one-third of energy use globally. A variety of optimization methods have been proposed for building energy management, which are mainly divided into two types: model-based and model-free. READ MORE
