Sökning: "reinforcement learning"

Visar resultat 6 - 10 av 237 uppsatser innehållade orden reinforcement learning.

  1. 6. Insights into Model-Agnostic Meta-Learning on Reinforcement Learning Tasks

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

    Författare :Konstantinos Saitas-Zarkias; [2021]
    Nyckelord :Meta-Learning; Reinforcement Learning; Deep Learning;

    Sammanfattning : Meta-learning has been gaining traction in the Deep Learning field as an approach to build models that are able to efficiently adapt to new tasks after deployment. Contrary to conventional Machine Learning approaches, which are trained on a specific task (e. LÄS MER

  2. 7. Anomalidetektering i loggar med förstärkt inlärning

    Kandidat-uppsats, Karlstads universitet/Fakulteten för hälsa, natur- och teknikvetenskap (from 2013)

    Författare :Sofia Lantz; [2021]
    Nyckelord :Maskininlärning; Anomalidetektering; Förstärkt inlärning; Logganalys;

    Sammanfattning : By using machine learning to monitor and find deviations in log data makes it easier for developers and can prevent a workflow from stopping. The goal of this project is to investigate if it is possible to find anomalies in log data using reinforcement learning. LÄS MER

  3. 8. Deep reinforcement learning for real-time power grid topology optimization

    Kandidat-uppsats, Lunds universitet/Matematisk statistik

    Författare :Jacob Rothschild; [2021]
    Nyckelord :Deep reinforcement learning; Dueling Deep Q-Network; electricity transmission network; real-time topology optimization; sustainable energy; Mathematics and Statistics;

    Sammanfattning : In our pursuit of carbon neutrality, drastic changes to generation and consumption of electricity will cause new and complex demands on the power grid and its operators. A cheap, promising, and under-exploited mitigation is real-time power grid topology optimization (RTTO). LÄS MER

  4. 9. Deep Reinforcement Learning for Autonomous Highway Driving Scenario

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

    Författare :Neil Pradhan; [2021]
    Nyckelord :Deep reinforcement learning; Highway driving scenario; Tactical decision making; fuel reduction; high-level decision making; autonomous driving; Partially Observable Markov Decision Process POMDP .; Lärande om djupförstärkning; motorvägsscenario; taktiskt beslutsfattande; bränslereduktion; beslut på hög nivå; autonom körning; Partially Observable Markov Decision Process POMDP ;

    Sammanfattning : We present an autonomous driving agent on a simulated highway driving scenario with vehicles such as cars and trucks moving with stochastically variable velocity profiles. The focus of the simulated environment is to test tactical decision making in highway driving scenarios. LÄS MER

  5. 10. Maskininlärningsmetoder tillämpade på StarCraft 2 - En undersökning av reinforcement och imitation learning

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

    Författare :JONATHAN BERGQVIST; CARL CLAESSON; PONTUS ELIASSON; ADAM GRANDÉN; EDVIN LAM; ARVID LUNDBERG; [2020-10-29]
    Nyckelord :;

    Sammanfattning : Inom artificiell intelligens, som kontinuerligt utvecklas, har maskininlärning tagit en centralroll. Medan regelbaserad AI varit tillräcklig för att lösa grundläggande uppgifter behöverdagens utmaningar mer avancerade metoder. LÄS MER