Sökning: "mobile agent"

Visar resultat 1 - 5 av 62 uppsatser innehållade orden mobile agent.

1. 1. Simulating Mobility of Large Population using Mobile Application Data

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

   Författare :Mattias Rydström; Diana Salim; [2024-01-23]
   Nyckelord :Human mobility; mobile application data; synthesize activity plans;

   Sammanfattning : Understanding people’s travel patterns and knowing the frequency of their travel activities provide important insights for effective transport management and infrastructure planning. While traditional travel surveys have historically contributed to this valuable information, they come with shortcomings such as being expensive to collect, easily outdated, and having short time coverage. LÄS MER

3. 2. Deep Reinforcement Learning in Games Based on Extracted Features

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

   Författare :Emilia Sjögren; Erika Weidenhaijn; [2023]
   Nyckelord :;

   Sammanfattning : FlappyBird is a popular mobile game that captured many people's attention because itwas easy to understand but difficult to perform --- players were often right on the edge ofsucceeding, which led to a strong desire to play again. The purpose of this project is to investigatethe possibility of using a neural network trained with reinforcement learning to play the game usingextracted features rather than raw images. LÄS MER

4. 3. 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

5. 4. Mobile Traffic Classification and Multi-Cell Base Station Control for Energy-Efficient 5G Networks

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

   Författare :Cai Tianzhang; [2023]
   Nyckelord :;

   Sammanfattning : The global energy consumption of mobile networks is rapidly increasing due to the exponential growth of mobile network traffic. The advent of next-generation cellular technologies such as fifth-generation (5G) and beyond promises higher network throughput and lower latency but also demands higher power consumption for its denser base station (BS) deployment and more energy-intensive processors. LÄS MER

7. 5. Deep Reinforcement Learning on Social Environment Aware Navigation based on Maps

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

   Författare :Victor Sanchez; [2023]
   Nyckelord :Deep Reinforcement Learning; Environment-aware navigation; Robotics; Artificial Intelligence; Apprentissage par renforcement profond; Navigation consciente de l’humain; Intelligence Artificielle; Robotique; Djup Förstärkande Inlärning; Människomedveten navigering; Robotik; Artificiell Intelligens;

   Sammanfattning : Reinforcement learning (RL) has seen a fast expansion in recent years of its successful application to a range of decision-making and complex control tasks. Moreover, deep learning offers RL the opportunity to enlarge its spectrum of complex fields. LÄS MER