Sökning: "Offline Reinforcement Learning"

Visar resultat 1 - 5 av 11 uppsatser innehållade orden Offline Reinforcement Learning.

  1. 1. An Empirical Survey of Bandits in an Industrial Recommender System Setting

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Tobias Schwarz; Johan Brandby; [2023-09-21]
    Nyckelord :computer science; industrial application; machine learning; reinforcement learning; multi-armed bandits; MAB; contextual multi-armed bandits; survey; batch learning;

    Sammanfattning : In this thesis, the effects of incorporating unstructured data—images in the wild—in contextual multi-armed bandits are investigated, when used within a recommender system setting, which focuses on picture-based content suggestion. The idea is to employ image features, extracted by a pre-trained convolutional neural network, and study the resulting bandit behaviors when including respective excluding this information in the typical context creation, which normally relies on structured data sources—such as metadata. LÄS MER

  2. 2. Transformer Offline Reinforcement Learning for Downlink Link Adaptation

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

    Författare :Alexander Mo; [2023]
    Nyckelord :Link Adaptation; Transformers; Reinforcement Learning; Sequence Modelling; Decision Transformer; Deep Neural Networks; Radio Resource Management; Telecommunication; Länkanpassning; Transformers; Reinforcement Learning; Sekvensmodellering; Beslutsstöd; Djupa neurala nätverk; Dataresurshantering; Telekommunikation;

    Sammanfattning : 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). LÄS MER

  3. 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)

    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. 4. Data-Driven Adaptive Control of Unmanned Surface Vehicles Using Learning-Based Model Predictive Control

    Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknik

    Författare :Markus Svedberg; [2023]
    Nyckelord :Technology and Engineering;

    Sammanfattning : In this thesis, the subject of data-driven control of Unmanned Surface Vehicles (USVs) is explored. The control task is formulated through Nonlinear Model Predictive Path Following Control (NMPFC). System identification (SYSID) and Reinforcement Learning (RL) are employed to improve performance in a data-driven manner. LÄS MER

  5. 5. Offline Reinforcement Learning for Optimization of Therapy Towards a Clinical Endpoint

    Master-uppsats, KTH/Medicinteknik och hälsosystem

    Författare :Simon Jenner; [2022]
    Nyckelord :Offline; Reinforcement learning; Double Deep Q-Network; Cognitive behavior therapy; Digital therapeutics; Optimization; Förstärkningsinlärning; Dubbelt djupt Q-nätverk; Kognitiv beteendeterapi; Digital terapeutika; Optimering;

    Sammanfattning : The improvement of data acquisition and computer heavy methods in recentyears has paved the way for completely digital healthcare solutions. Digitaltherapeutics (DTx) are such solutions and are often provided as mobileapplications that must undergo clinical trials. LÄS MER