Sökning: "Djupa Q-nätverk"

Hittade 4 uppsatser innehållade orden Djupa Q-nätverk.

1. 1. Stabilizing Side Effects of Experience Replay With Different Network Sizes for Deep Q-Network

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

   Författare :Simon Granström; [2023]
   Nyckelord :;

   Sammanfattning : This report investigates the effects of two different types of batch selection used for traininga Deep Reinforcement Learning agent in games. More specifically, the impact of thedifferent methods were tested for different sizes of Deep Neural Networks while using theDeep Q-Network (DQN) algorithm. LÄS MER

3. 2. Investigating Multi-Objective Reinforcement Learning for Combinatorial Optimization and Scheduling Problems : Feature Identification for multi-objective Reinforcement Learning models

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

   Författare :Rikard Fridsén Skogsberg; [2022]
   Nyckelord :Multi-Objective Reinforcement Learning; Radio Resource Scheduling; Deep Q-Networks; Single-policy; Multi-policy; Scalarization.; Flermåls förstärkningsinlärning; Radio resurs schemaläggning; Djupa Q-nätverk; Enskilt mål; Flermål;

   Sammanfattning : Reinforcement Learning (RL) has in recent years become a core method for sequential decision making in complex dynamical systems, being of great interest to support improvements in scheduling problems. This could prove important to areas in the newer generation of cellular networks. LÄS MER

4. 3. Extracting Behaviour Trees from Deep Q-Networks : Using learning from demostration to transfer knowledge between models.

   Master-uppsats, Linköpings universitet/Artificiell intelligens och integrerade datorsystem

   Författare :Zacharias Nordström; [2020]
   Nyckelord :Behaviour tree; deep q-network; extraction;

   Sammanfattning : In recent years the advancement in machine learning have solved more and more complex problems. But still these techniques are not commonly used in the industry. One problem is that many of the techniques are black boxes, it is hard to analyse them to make sure that their behaviour is safe. LÄS MER

5. 4. Integrating Reinforcement Learning into Behavior Trees by Hierarchical Composition

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

   Författare :Mart Kartasev; [2019]
   Nyckelord :;

   Sammanfattning : This thesis investigates ways to extend the use of Reinforcement Learning (RL) to Behavior Trees (BTs). BTs are used in the field of Artificial Intelligence (AI) in order to create modular and reactive planning agents. LÄS MER