Sökning: "DQN"
Visar resultat 1 - 5 av 49 uppsatser innehållade ordet DQN.
1. Evaluation of Deep Q-Learning Applied to City Environment Autonomous Driving
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och systemSammanfattning : This project’s goal was to assess both the challenges of implementing the Deep Q-Learning algorithm to create an autonomous car in the CARLA simulator, and the driving performance of the resulting model. An agent was trained to follow waypoints based on two main approaches. LÄS MER
2. Federated Machine Learning for Resource Allocation in Multi-domain Fog Ecosystems
Master-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : 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
3. 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)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. Stabilizing Side Effects of Experience Replay With Different Network Sizes for Deep Q-Network
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This report investigates the effects of two different types of batch selection used for traininga Deep Reinforcement Learning agent in games. More specifically, the impact of thedifferent methods were tested for different sizes of Deep Neural Networks while using theDeep Q-Network (DQN) algorithm. LÄS MER
5. Reinforcement Learning for Pickup and Delivery Systems
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)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