Essays about: "Deep reinforcement learning"
Showing result 6 - 10 of 201 essays containing the words Deep reinforcement learning.
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6. Transformer Offline Reinforcement Learning for Downlink Link Adaptation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Recent advancements in Transformers have unlocked a new relational analysis technique for Reinforcement Learning (RL). This thesis researches the models for DownLink Link Adaptation (DLLA). READ MORE
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7. Multi-Agent Deep Reinforcement Learning in Warehouse Environments
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This report presents a deep reinforcement algorithm for multi-agent systems based on the classicalDeep Q-Learning algorithm. The method considers a decentralized approach to controlling theagents, by equipping each agent with its own neural network and replay memory. READ MORE
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8. Reinforcement learning for EV charging optimization : A holistic perspective for commercial vehicle fleets
University essay from KTH/Skolan för industriell teknik och management (ITM)Abstract : Recent years have seen an unprecedented uptake in electric vehicles, driven by the global push to reduce carbon emissions. At the same time, intermittent renewables are being deployed increasingly. These developments are putting flexibility measures such as dynamic load management in the spotlight of the energy transition. READ MORE
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9. Deep Reinforcement Learning in Games Based on Extracted Features
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : FlappyBird is a popular mobile game that captured many people's attention because itwas easy to understand but difficult to perform --- players were often right on the edge ofsucceeding, which led to a strong desire to play again. The purpose of this project is to investigatethe possibility of using a neural network trained with reinforcement learning to play the game usingextracted features rather than raw images. READ MORE
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10. Decreasing Training Time of Reinforcement Learning Agents for Remote Tilt Optimization using a Surrogate Neural Network Approximator
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : One possible application of reinforcement learning in the telecommunication field is antenna tilt optimization. However, one of key challenges we face is that the use of handcrafted simulators as environments to provide information for agents is often time-consuming regarding training reinforcement learning agents. READ MORE
