Sökning: "Reinforcement learning"

Visar resultat 11 - 15 av 457 uppsatser innehållade orden Reinforcement learning.

1. 11. Multi-Agent Deep Reinforcement Learning in Warehouse Environments

   Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :John Cao; Mikael Hammarling; [2023]
   Nyckelord :;

   Sammanfattning : 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. LÄS MER

3. 12. Reinforcement learning for EV charging optimization : A holistic perspective for commercial vehicle fleets

   Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

   Författare :Enzo Alexander Cording; [2023]
   Nyckelord :Deep Reinforcement Learning; EV charging optimization; Artificial Intelligence; Commercial vehicle fleets; Electric vehicles; Deep Reinforcement Learning; optimering av elbilsladdning; artificiell intelligens; kommersiella fordonsflottor; Elektriska fordon;

   Sammanfattning : 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. LÄS MER

4. 13. Deep Reinforcement Learning in Games Based on Extracted Features

   Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Emilia Sjögren; Erika Weidenhaijn; [2023]
   Nyckelord :;

   Sammanfattning : 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. LÄS MER

5. 14. Decreasing Training Time of Reinforcement Learning Agents for Remote Tilt Optimization using a Surrogate Neural Network Approximator

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Jiaming Huang; [2023]
   Nyckelord :;

   Sammanfattning : 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. LÄS MER

7. 15. Federated Machine Learning for Resource Allocation in Multi-domain Fog Ecosystems

   Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Weilin Zhang; [2023]
   Nyckelord :Workload Allocation; Federated Learning; Deep Q-network; Fog networks; Federated Average Aggregation;

   Sammanfattning : The proliferation of the Internet of Things (IoT) has increasingly demanded intimacy between cloud services and end-users. This has incentivised extending cloud resources to the edge in what is deemed fog computing. The latter is manifesting as an ecosystem of connected clouds, geo-dispersed and of diverse capacities. LÄS MER