Sökning: "Q-Learning"

Visar resultat 21 - 25 av 95 uppsatser innehållade ordet Q-Learning.

1. 21. Energy Efficient Communication Scheduling for IoT-based Waterbirds Monitoring: Decentralized Strategies

   Master-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Författare :Otabek Sobirov; [2022]
   Nyckelord :TSCH; 6TiSCH; RPL; scheduling; energy consumption; COOJA; autonomous scheduling; distributed scheduling; reinforcement learning; RL-based scheduling; Q-Learning;

   Sammanfattning : Monitoring waterbirds have several benefits, including analyzing the number of endangered species, giving a reliable indication of public health, etc. Monitoring waterbirds in their habitat is a challenging task since the location is distant, and the collection of monitoring data requires large bandwidth. LÄS MER

3. 22. Deep Reinforcement Learning and Simulation for the Optimization of Production Systems

   Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Siyuan Chen; [2022]
   Nyckelord :;

   Sammanfattning : The main objective of this master thesis project is to use the deep reinforcement learning (DRL) and simulation method for optimization of production systems. In this project, the Deep Q-learning Networks (DQN) algorithm is first used to optimize seven decision variables in Averill Law’s production system to find the best profit, with 99. LÄS MER

4. 23. Learning medical triage by using a reinforcement learning approach

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Niklas Sundqvist; [2022]
   Nyckelord :machine learning; reinforcement learning; medical triage; q-learning; deep q-learning; double deep q-learning;

   Sammanfattning : Many emergency departments are today suffering from a overcrowding of people seeking care. The first stage in seeking care is being prioritised in different orders depending on symptoms by a doctor or nurse called medical triage. This is a cumbersome process that could be subject of automatisation. LÄS MER

5. 24. 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

7. 25. Graph Bandits : Multi-Armed Bandits with Locality Constraints

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

   Författare :Kasper Johansson; [2022]
   Nyckelord :Multi-armed bandits; locality constraints; reinforcement learning; Flerarmade banditer; lokala restriktioner; förstärkningsinlärning;

   Sammanfattning : Multi-armed bandits (MABs) have been studied extensively in the literature and have applications in a wealth of domains, including recommendation systems, dynamic pricing, and investment management. On the one hand, the current MAB literature largely seems to focus on the setting where each arm is available to play at each time step, and ignores how agents move between the arms. LÄS MER