Sökning: "DDQN"

Visar resultat 1 - 5 av 6 uppsatser innehållade ordet DDQN.

1. 1. Offline Reinforcement Learning for Optimization of Therapy Towards a Clinical Endpoint

   Master-uppsats, KTH/Medicinteknik och hälsosystem

   Författare :Simon Jenner; [2022]
   Nyckelord :Offline; Reinforcement learning; Double Deep Q-Network; Cognitive behavior therapy; Digital therapeutics; Optimization; Förstärkningsinlärning; Dubbelt djupt Q-nätverk; Kognitiv beteendeterapi; Digital terapeutika; Optimering;

   Sammanfattning : The improvement of data acquisition and computer heavy methods in recentyears has paved the way for completely digital healthcare solutions. Digitaltherapeutics (DTx) are such solutions and are often provided as mobileapplications that must undergo clinical trials. LÄS MER

3. 2. Reinforcement Learning for Market Making

   Master-uppsats, KTH/Matematisk statistik

   Författare :Simon Carlsson; August Regnell; [2022]
   Nyckelord :Reinforcement learning; Market making; Deep reinforcement learning; Limit order book; Algorithmic trading; High-frequency trading; Machine learning; Artificial intelligence; Q-learning; DDQN; Förstärkningsinlärning; Market making; Djup förstärkningsinlärning; Limitorderbok; Algoritmisk handel; Högfrekvenshandel; Maskininlärning; Artificiell intelligens; Q-learning; DDQN;

   Sammanfattning : Market making – the process of simultaneously and continuously providing buy and sell prices in a financial asset – is rather complicated to optimize. Applying reinforcement learning (RL) to infer optimal market making strategies is a relatively uncharted and novel research area. LÄS MER

4. 3. Deep Reinforcement Learning for Building Control : A comparative study for applying Deep Reinforcement Learning to Building Energy Management

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

   Författare :Wanfu Zheng; [2022]
   Nyckelord :Deep Reinforcement Learning; Building Control; Building Energy Management; Optimization; Thermal Discomfort; Operational Cost; Deep Reinforcement Learning; byggnadskontroll; Building Energy Management; optimering; termiskt obehag; driftskostnader;

   Sammanfattning : Energy and environment have become hot topics in the world. The building sector accounts for a high proportion of energy consumption, with over one-third of energy use globally. A variety of optimization methods have been proposed for building energy management, which are mainly divided into two types: model-based and model-free. LÄS MER

5. 4. Deep Reinforcement Learning for the Popular Game tag

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

   Författare :August Söderlund; Gustav von Knorring; [2021]
   Nyckelord :Reinforcement Learning; Neural Networks; Qlearning; Deep Q-learning; Double Deep Q-learning; Dual-agent Training.;

   Sammanfattning : Reinforcement learning can be compared to howhumans learn – by interaction, which is the fundamental conceptof this project. This paper aims to compare three differentlearning methods by creating two adversarial reinforcementlearning models and simulate them in the game tag. LÄS MER

7. 5. Research on Dynamic Offloading Strategy of Satellite Edge Computing Based on Deep Reinforcement Learning

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

   Författare :Rui Geng; [2021]
   Nyckelord :Deep reinforcement learning; Satellite edge computing; Offloading strategy; Djup Förstärkning Lärande; Satellit Kant Datoranvändning; Avlastning Strategi;

   Sammanfattning : Nowadays more and more data is generated at the edge of the network, and people are beginning to consider decentralizing computing tasks to the edge of the network. The network architecture of edge computing is different from the traditional network architecture. LÄS MER