Sökning: "deep Q-network"

Visar resultat 6 - 10 av 45 uppsatser innehållade orden deep Q-network.

1. 6. Reinforcement Learning for Pickup and Delivery Systems

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

   Författare :Erika Sandhagen; Sarah Magnusson; [2023]
   Nyckelord :;

   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

3. 7. Creating an AI opponent withsuper-human performance for Splendor

   Uppsats för yrkesexamina på avancerad nivå, Örebro universitet/Institutionen för naturvetenskap och teknik

   Författare :Jonatan Simonsson; [2023]
   Nyckelord :;

   Sammanfattning : This project is in collaboration with Piktiv AB. The purpose of the project is tocreate a reinforcement learning agent capable of reaching super human performancein the board game Splendor.Three agents was implemented using a Double Deep Q-Network and certain improvements to the architecture. LÄS MER

4. 8. Multi-Agent Control in Warehousing: A Deep Q-Network Approach

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

   Författare :Adam Fischer; Martin Wilén; [2023]
   Nyckelord :;

   Sammanfattning : With an increase in consumption, warehouses increase in size and demand for fastdistribution of goods. One solution to this problem is self learning robots that can adapt toany warehouse. LÄS MER

5. 9. Playing Atari Breakout Using Deep Reinforcement Learning

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

   Författare :Jonas Nils Martin Lidman; Simon Jonsson; [2022]
   Nyckelord :Reinforcement learning; CartPole; Breakout; DQN;

   Sammanfattning : This report investigates the implementation of a Deep Reinforcement Learning (DRL) algorithm for complex tasks. The complex task chosen was the classic game Breakout, first introduced on the Atari 2600 console.The selected DRL algorithm was Deep Q-Network(DQN) since it is one of the first and most fundamental DRL algorithms. LÄS MER

7. 10. Deep reinforcement learning for isocenter placement in Gamma Knife® radiosurgery

   Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Dmitrijs Kass; [2022]
   Nyckelord :;

   Sammanfattning : Disposition of isocenters inside the brain tumor is of paramount importance for the quality of the Leksell Gamma Knife® radiosurgery. This work presents a novel approach based on deep reinforcement learning aimed at optimizing isocenter locations. LÄS MER