Sökning: "markov decision process"

Visar resultat 21 - 25 av 50 uppsatser innehållade orden markov decision process.

  1. 21. 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

  3. 22. Deep Reinforcement Learning for the Optimization of Combining Raster Images in Forest Planning

    Master-uppsats, Mittuniversitetet/Institutionen för informationssystem och –teknologi

    Författare :Yangyang Wen; [2021]
    Nyckelord :Raster images; Optimization; Deep Reinforcement Learning; Markov Decision Process; Deep Q Learning Neural Network; Temporal Difference; Model Usefulness; Parameter Correlation; Model Effectiveness.;

    Sammanfattning : Raster images represent the treatment options of how the forest will be cut. Economic benefits from cutting the forest will be generated after the treatment is selected and executed. Existing raster images have many clusters and small sizes, this becomes the principal cause of overhead. LÄS MER

  4. 23. Deep Reinforcement Learning in Cart Pole and Pong

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

    Författare :Dennis Kuurne Uussilta; Viktor Olsson; [2020]
    Nyckelord :Artificial Intelligence; Machine Learning; Rein-forcement Learning; Deep Q-learning Network; CartPole; Pong;

    Sammanfattning : In this project, we aim to reproduce previous resultsachieved with Deep Reinforcement Learning. We present theMarkov Decision Process model as well as the algorithms Q-learning and Deep Q-learning Network (DQN). We implement aDQN agent, first in an environment called CartPole, and later inthe game Pong. LÄS MER

  5. 24. Normalizing Flow based Hidden Markov Models for Phone Recognition

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

    Författare :Anubhab Ghosh; [2020]
    Nyckelord :Phone recognition; generative learning; Normalizing flows; Decision fusion; Speech recognition;

    Sammanfattning : The task of Phone recognition is a fundamental task in Speech recognition and often serves a critical role in bench-marking purposes. Researchers have used a variety of models used in the past to address this task, using both generative and discriminative learning approaches. LÄS MER

  7. 25. Intelligent Charging Algorithm for Electric Vehicles

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

    Författare :Jacob Sörme; [2020]
    Nyckelord :;

    Sammanfattning : Electric vehicles play an important role in creating a fossil free transport sector. Making the vehicles efficient involves many new areas outside the manufacturing process, such as chargers, power grids and electricity markets. LÄS MER