Sökning: "reinforcement learning"

Visar resultat 1 - 5 av 284 uppsatser innehållade orden reinforcement learning.

  1. 1. MIXED MEMORY Q-LEARNER An adaptive reinforcement learning algorithm for the Iterated Prisoner’s Dilemma

    Kandidat-uppsats, Institutionen för tillämpad informationsteknologi

    Författare :Anna Dollbo; [2021-09-21]
    Nyckelord :Machine learning; reinforcement learning; game theory; iterated prisoner’s dilemma; state representation; Q-learning;

    Sammanfattning : The success of future societies is likely to depend on cooperative interactionsbetween humans and artificial agents. As such, it is important to investigate howmachines can learn to cooperate. LÄS MER

  2. 2. Deep Reinforcement LearningA case study of AlphaZero

    Kandidat-uppsats, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Fredrik Mattisson; [2021]
    Nyckelord :;

    Sammanfattning : Using deep neural networks for reinforcement learning has proven very successful, as demonstrated by the AlphaZero algorithm developed by DeepMind in 2018. This algorithm is capable of mastering two-player zero-sum board games entirely by playing against itself. LÄS MER

  3. 3. Deep Reinforcement Learning for Temperature Control in Buildings and Adversarial Attacks

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

    Författare :Kevin Ammouri; [2021]
    Nyckelord :Deep Reinforcement Learning; Adversarial Attacks; Optimal Attacks; Building Control; Optimal Control; Energy Efficiency; Djup förstärkande inlärning; Adversarial Attacker; Optimala Attacker; Byggnadskontroll; Optimal Kontroll; Energieffektivitet;

    Sammanfattning : Heating, Ventilation and Air Conditioning (HVAC) systems in buildings are energy consuming and traditional methods used for building control results in energy losses. The methods cannot account for non-linear dependencies in the thermal behaviour. LÄS MER

  4. 4. Exploring feasibility of reinforcement learning flight route planning

    Kandidat-uppsats, Linköpings universitet/Institutionen för datavetenskap; Linköpings universitet/Filosofiska fakulteten

    Författare :Axel Wickman; [2021]
    Nyckelord :SAAB; flight route planning; autorouting; auto-routing; auto routing; AI; machine learning; fighter jet; convolution; PPO; DQN; Astar; A*; C ; Python; LibTorch; PyTorch; multi threading; multi-threading; simulation; aerodynamics; world generation; Perlin noise; investigation; reward; Flygplanering; flygruttsplannering; maskininlärning; AI; SAAB; faltning; faltningslager; belöning;

    Sammanfattning : This thesis explores and compares traditional and reinforcement learning (RL) methods of performing 2D flight path planning in 3D space. A wide overview of natural, classic, and learning approaches to planning s done in conjunction with a review of some general recurring problems and tradeoffs that appear within planning. LÄS MER

  5. 5. Adaptive network selection for moving agents using deep reinforcement learning

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

    Författare :William Skagerström; [2021]
    Nyckelord :;

    Sammanfattning : With the rapid development and deployment of “Internet of Things”-devices comes a new era of benefits to increase the efficiency of our everyday lives. Many of these devices rely on having an established network connection in order to operate at peak performance, but this requirement could be hard to guarantee in the face of less supported infrastructure in certain parts of the world. LÄS MER