Sökning: "Q – policy"

Visar resultat 1 - 5 av 66 uppsatser innehållade orden Q – policy.

  1. 1. Optimal taxation by two-agent reinforcement learning

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Erik Lindau; [2023]
    Nyckelord :;

    Sammanfattning : An economy’s tax policy is one of the vital moments for, on the one hand, stimulating economic growth and labor, and, on the other hand gaining revenues from economic performance. A sufficient level of tax revenues is further important to keep up with governmental obligations and social welfare. LÄS MER

  3. 2. Explainable AI for Multi-Agent Control Problem

    Master-uppsats, Mälardalens universitet/Akademin för innovation, design och teknik

    Författare :Hanna Prokopova; [2023]
    Nyckelord :;

    Sammanfattning : This report presents research on the application of policy explanation techniques in the context of coordinated reinforcement learning (CRL) for mobile network optimization. The goal was to improve the interpretability and comprehensibility of decision-making processes in multi-agent environments, with a particular focus on the Remote Antenna Tilt (RET) problem. LÄS MER

  4. 3. S-MARL: An Algorithm for Single-To-Multi-Agent Reinforcement Learning : Case Study: Formula 1 Race Strategies

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

    Författare :Marinaro Davide; [2023]
    Nyckelord :Reinforcement Learning; Single-to-Multi-Agent; Learning Stability; Exploration-Exploitation trade-off; Race Strategy Optimization; Förstärkningsinlärning; Från en till flera agenter; Stabilitet vid inlärning; Utforskning-exploatering; Optimering av tävlingsstrategier;

    Sammanfattning : A Multi-Agent System is a group of autonomous, intelligent, interacting agents sharing an environment that they observe through sensors, and upon which they act with actuators. The behaviors of these agents can be either defined upfront by programmers or learned by trial-and-error resorting to Reinforcement Learning. LÄS MER

  5. 4. Control Method for an Automated Forest Machine Based on Deep Reinforcement Learning

    Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

    Författare :Youchen Sun; [2023]
    Nyckelord :;

    Sammanfattning : An automated forest machine was designed in order to improve the working environment of today’s forest machine operators. In order to realize the autonomous control of the forest machine, model-based methods such as A* and dynamic window were used in previous projects. LÄS MER

  7. 5. Scalable Reinforcement Learning for Linear-Quadratic Control of Networks

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

    Författare :Johan Olsson; [2023]
    Nyckelord :Technology and Engineering;

    Sammanfattning : Distributed optimal control is known to be challenging and can become intractable even for linear-quadratic regulator problems. In this work, we study a special class of such problems where distributed state feedback controllers can give near-optimal performance. LÄS MER