Sökning: "RL network"

Visar resultat 1 - 5 av 50 uppsatser innehållade orden RL network.

  1. 1. Evaluation of Deep Q-Learning Applied to City Environment Autonomous Driving

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och system

    Författare :Jonas Wedén; [2024]
    Nyckelord :Machine Learning; ML; Reinforcement Learning; RL; Neural Network; Deep Learning; Autonomous Vehicle; Vehicle; CARLA; Convolutional Neural Network; CNN; Precisit; Q-learning; Deep Q-learning; DQN;

    Sammanfattning : 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. 2. LEO Satellite Connectivity for flying vehicles

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

    Författare :Jinxuan Chen; [2023]
    Nyckelord :LEO satellite network; satellite connectivity strategy; Nash-SAC; flying vehicles; LEO:s satellitnät; Strategi för satellitanslutning; Nash-SAC; flygande fordon;

    Sammanfattning : Compared with the terrestrial network (TN), which can only support limited covered areas, satellite communication (SC) can provide global coverage and high survivability in case of an emergency like an earthquake. Especially low-earth orbit (LEO) satellites, as a promising technology, which is integral to achieving the goal of global seamless coverage and reliable communication, catering to 6G’s communication requirements. LÄS MER

  3. 3. 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

  4. 4. Machine Learning-Based Instruction Scheduling for a DSP Architecture Compiler : Instruction Scheduling using Deep Reinforcement Learning and Graph Convolutional Networks

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

    Författare :Lucas Alava Peña; [2023]
    Nyckelord :Instruction Scheduling; Deep reinforcement Learning; Compilers; Graph Convolutional Networks; Schemaläggning av instruktioner; Deep Reinforcement Learning; kompilatorer; grafkonvolutionella nätverk;

    Sammanfattning : Instruction Scheduling is a back-end compiler optimisation technique that can provide significant performance gains. It refers to ordering instructions in a particular order to reduce latency for processors with instruction-level parallelism. LÄS MER

  5. 5. Time synchronization error detection in a radio access network

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

    Författare :Moulika Madana; [2023]
    Nyckelord :GNSS - Global Navigation Satellite System; OAS - Over-the air-synchronization; PRTC - primary reference time clock; PTP - precision time protocol; Gauss Jordan elimination; GNN- Graph Neural Network; GNSS -Globalt navigationssatellitsystem; OAS - Över-the-air tidssynkronisering; PRTC - Primär referenstidklocka; PTP - Precisionstidprotokoll; Gauss Jordan eliminering; GNN- Graf neurala nätverk;

    Sammanfattning : Time synchronization is a process of ensuring all the time difference between the clocks of network components(like base stations, boundary clocks, grandmasters, etc.) in the mobile network is zero or negligible. It is one of the important factors responsible for ensuring effective communication between two user-equipments in a mobile network. LÄS MER