Sökning: "RL"
Visar resultat 11 - 15 av 132 uppsatser innehållade ordet RL.
11. Deep Reinforcement Learning on Social Environment Aware Navigation based on Maps
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)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
12. Scalable Reinforcement Learning for Formation Control with Collision Avoidance : Localized policy gradient algorithm with continuous state and action space
Master-uppsats, KTH/Skolan för teknikvetenskap (SCI); KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In the last decades, significant theoretical advances have been made on the field of distributed mulit-agent control theory. One of the most common systems that can be modelled as multi-agent systems are the so called formation control problems, in which a network of mobile agents is controlled to move towards a desired final formation. LÄS MER
13. Data-Driven Adaptive Control of Unmanned Surface Vehicles Using Learning-Based Model Predictive Control
Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknikSammanfattning : In this thesis, the subject of data-driven control of Unmanned Surface Vehicles (USVs) is explored. The control task is formulated through Nonlinear Model Predictive Path Following Control (NMPFC). System identification (SYSID) and Reinforcement Learning (RL) are employed to improve performance in a data-driven manner. LÄS MER
14. Reinforcement Learning for Pickup and Delivery Systems
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In this project multi-agent reinforcement learning (RL) for a warehouse environmentwith robots delivering packages has been studied. This was done by first implementing the RLalgorithm Q-learning and investigating how the parameters of Q-learning affect the performanceof the algorithm. LÄS MER
15. Improving Co-existence of URLLC and Distributed AI using RL
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In 5G, Ultra-reliable and low-Latency communications (URLLC) service is envisioned to enable use cases with strict reliability and latency requirements on wireless communication. For the upcoming 6G network, machine learning (ML) also stands an important role that introduces intelligence and further enhances the system performance. LÄS MER