Sökning: "reinforcement learning and recurrent reinforcement learning"

Visar resultat 1 - 5 av 8 uppsatser innehållade orden reinforcement learning and recurrent reinforcement learning.

1. 1. Safe Reinforcement Learning for Social Human-Robot Interaction : Shielding for Appropriate Backchanneling Behavior

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

   Författare :Mohamed Akif; [2023]
   Nyckelord :Human-Robot Interaction; Backchanneling; Social Robots; Safe Reinforcement Learning; Shielding; Recurrent Neural Network; Gated Recurrent Unit; Människa-Robot Interaktion; Uppbackning; Sociala Robotar; Säker Förstärkningsinlärning; Avskärmning; Återkommande Neurala Nätverk; Gated Återkommande Enhet;

   Sammanfattning : Achieving appropriate and natural backchanneling behavior in social robots remains a challenge in Human-Robot Interaction (HRI). This thesis addresses this issue by utilizing methods from Safe Reinforcement Learning in particular shielding to improve social robot backchanneling behavior. LÄS MER

3. 2. Learning to Search for Targets : A Deep Reinforcement Learning Approach to Visual Search in Unseen Environments

   Master-uppsats, Linköpings universitet/Statistik och maskininlärning

   Författare :Oskar Lundin; [2022]
   Nyckelord :visual search; reinforcement learning; deep learning; computer vision; autonomous systems; visuell sökning; förstärkningsinlärning; djupinlärning; datorseende; autonoma system;

   Sammanfattning : Visual search is the perceptual task of locating a target in a visual environment. Due to applications in areas like search and rescue, surveillance, and home assistance, it is of great interest to automate visual search. LÄS MER

4. 3. Application of Deep Q-learning for Vision Control on Atari Environments

   Master-uppsats, Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisation

   Författare :Jim Öhman; [2021]
   Nyckelord :Reinforcement learning; Atari 2600; Deep Q-learning; Myopic Agents; Vision Control; Physics and Astronomy;

   Sammanfattning : The success of Reinforcement Learning (RL) has mostly been in artificial domains, with only some successful real-world applications. One of the reasons being that most real-world domains fail to satisfy a set of assumptions of RL theory. LÄS MER

5. 4. Modelling CLV in the Insurance Industry Using Deep Learning Methods

   Master-uppsats, KTH/Matematisk statistik

   Författare :Marta Jablecka; [2020]
   Nyckelord :Insurance; CLV; RNN; LSTM; GRU; DQL; Försäkring; CLV; RNN; LSTM; GRU; DQL;

   Sammanfattning : This paper presents a master’s thesis project in which deep learning methods are used to both calculate and subsequently attempt to maximize Customer Lifetime Value (CLV) for an insurance provider’s customers. Specifically, the report investigates whether panel data comprised of customers monthly insurance policy subscription history can be used with Recurrent Neural Networks (RNN) to achieve better predictive performance than the naïve forecasting model. LÄS MER

7. 5. Single asset trading: a recurrent reinforcement learning approach

   Kandidat-uppsats, Mälardalens högskola/Akademin för utbildning, kultur och kommunikation

   Författare :Marko Nikolic; [2020]
   Nyckelord :Nyckelord är; machine learning; reinforcement learning and recurrent reinforcement learning;

   Sammanfattning : Asset trading using machine learning has become popular within the financial industry in the recent years. This can for instance be seen in the large number of daily trading volume which are defined by an automatic algorithm. This thesis presents a recurrent reinforcement learning model to trade an asset. LÄS MER