Essays about: "Double Deep Q-learning"

Showing result 1 - 5 of 7 essays containing the words Double Deep Q-learning.

1. 1. Learning medical triage by using a reinforcement learning approach

   University essay from Uppsala universitet/Institutionen för informationsteknologi

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

   Abstract : 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. READ MORE

3. 2. Reinforcement Learning for Market Making

   University essay from KTH/Matematisk statistik

   Author : Simon Carlsson; August Regnell; [2022]
   Keywords : 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;

   Abstract : 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. READ MORE

4. 3. Board Game AI Using Reinforcement Learning

   University essay from Örebro universitet/Institutionen för naturvetenskap och teknik

   Author : Linus Strömberg; Viktor Lind; [2022]
   Keywords : Reinforcement Learning; Game Development; Computer Engineering; Q-learning 2;

   Abstract : The purpose of this thesis is to develop an agent that learns to play an interpretation ofthe popular game Ticket To Ride. This project is done in collaboration with Piktiv AB.This thesis presents how an agent based on the Double Deep Q-network algorithm learnsto play a version of Ticket To Ride using self-play. READ MORE

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

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

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

   Abstract : 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. READ MORE

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

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

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

   Abstract : 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. READ MORE