Sökning: "Deep Q-learning"

Visar resultat 6 - 10 av 58 uppsatser innehållade orden Deep Q-learning.

1. 6. Quantum Reinforcement Learning for Sensor-Assisted Robot Navigation Tasks

   Master-uppsats, Lunds universitet/Fysiska institutionen

   Författare :Joyce Cobussen; [2023]
   Nyckelord :Physics and Astronomy;

   Sammanfattning : Quantum computing has advanced rapidly throughout the past decade, both from a hardware and software point of view. A variety of algorithms have been developed that are suitable for the current generation of quantum devices, which are referred to as noisy intermediate-scale quantum devices. LÄS MER

3. 7. An efficient deep reinforcement learning approach to the energy management for a parallel hybrid electric vehicle

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

   Författare :Mingwei Liu; [2023]
   Nyckelord :HEV; EMS; Deep Reinforcement Learning; Learning Efficiency; Fuel Efficiency; HEV; EMS; Djup Förstärkningsinlärning; Inlärningseffektivitet; Bränsleeffektivitet;

   Sammanfattning : In contemporary world, the global energy crisis and raise of greenhouse gas concentration in atmosphere necessitate the energy conservation and emission reduction. Hybrid electric vehicles (HEVs) can achieve great promise in reducing fuel consumption and greenhouse gas emissions by appropriate energy management strategies (EMSs). LÄS MER

4. 8. Optimizing Energy Consumption in a Real-Time System Using Artificial Intelligence

   Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Caroline Lisa Pereira; [2023]
   Nyckelord :;

   Sammanfattning : In energy-efficient real-time embedded system design, the objective is to reduce energy consumption while meeting the tasks' timing requirements. Real-time Dynamic Voltage and Frequency Scaling (DVFS) methods aim at achieving this by scaling the frequency at which a single processor or multiple processors in the system operate, but they often assume that the tasks' deadlines are known and their arrival times are regular. LÄS MER

5. 9. Reinforcement Learning for Pickup and Delivery Systems

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

   Författare :Erika Sandhagen; Sarah Magnusson; [2023]
   Nyckelord :;

   Sammanfattning : In this project multi-agent reinforcement learning (RL) for a warehouse environmentwith robots delivering packages has been studied. This was done by first implementing the RLalgorithm Q-learning and investigating how the parameters of Q-learning affect the performanceof the algorithm. LÄS MER

7. 10. Modelling Cyber Security of Networks as a Reinforcement Learning Problem using Graphs : An Application of Reinforcement Learning to the Meta Attack Language

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

   Författare :Sandor Berglund; [2022]
   Nyckelord :Attack graphs; reinforcement learning; graph neural networks; Meta Attack Language; MAL; deepQ-learning DQN ; Attackgrafer; förstärningsinlärning; artificiella neuronnät; grafneuronnät; djup Qinlärning; Meta Attack Language; MAL;

   Sammanfattning : ICT systems are part of the vital infrastructure in today’s society. These systems are under constant threat and efforts are continually being put forth by cyber security experts to protect them. By applying modern AI methods, can these efforts both be improved and alleviated of the cost of expert work. LÄS MER