Sökning: "Deep Q-learning"

Visar resultat 1 - 5 av 26 uppsatser innehållade orden Deep Q-learning.

  1. 1. Application of Deep Q-learning for Vision Control on Atari Environments

    Master-uppsats, Lunds universitet/Beräkningsbiologi och biologisk fysik

    Författare :Jim Öhman; [2021]
    Nyckelord :Reinforcement learning; Atari 2600; Deep Q-learning; Myopic Agents; Vision Control; Physics and Astronomy;

    Sammanfattning : The success of Reinforcement Learning (RL) has mostly been in artificial domains, with only some successful real-world applications. One of the reasons being that most real-world domains fail to satisfy a set of assumptions of RL theory. LÄS MER

  2. 2. Deep Reinforcement Learning in Cart Pole and Pong

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

  3. 3. Reinforcement Learning Assisted Load Test Generation for E-commerce Applications

    Magister-uppsats, Mälardalens högskola/Akademin för innovation, design och teknik

    Författare :Golrokh Hamidi; [2020]
    Nyckelord :;

    Sammanfattning : Background: End-user satisfaction is not only dependent on the correct functioning of the software systems but is also heavily dependent on how well those functions are performed. Therefore, performance testing plays a critical role in making sure that the system responsively performs the indented functionality. LÄS MER

  4. 4. Scaling up Maximum Entropy Deep Inverse Reinforcement Learning with Transfer Learning

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

    Författare :Emil Broqvist Widham; [2020]
    Nyckelord :;

    Sammanfattning : In this thesis an issue with common inverse reinforcement learning algorithms is identified, which causes them to be computationally heavy. A solution is proposed which attempts to address this issue and which can be built upon in the future. LÄS MER

  5. 5. Distributed Optimization Through Deep Reinforcement Learning

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

    Författare :Mikaela Funkquist; Minghua Lu; [2020]
    Nyckelord :Reinforcement learning; Q-learning; Deep Q-learning; Artificial neural networks; robots; warehouse; agent;

    Sammanfattning : Reinforcement learning methods allows self-learningagents to play video- and board games autonomously. Thisproject aims to study the efficiency of the reinforcement learningalgorithms Q-learning and deep Q-learning for dynamical multi-agent problems. The goal is to train robots to optimally navigatethrough a warehouse without colliding. LÄS MER