Search for dissertations about: "Reinforcement Learning"

Showing result 16 - 20 of 172 swedish dissertations containing the words Reinforcement Learning.

2. 16. Terrain machine learning

   Author : Viktor Wiberg; Martin Servin; Tomas Nordfjell; Eddie Wadbro; Todor Stoyanov; Umeå universitet; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; LANTBRUKSVETENSKAPER; AGRICULTURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; multibody dynamics simulation; rough terrain vehicle; autonomous vehicles; robotics control; discrete element method; sim-to-real; reinforcement learning; fysik; Physics;

   Abstract : The use of heavy vehicles in rough terrain is vital in the industry but has negative implications for the climate and ecosystem. In addition, the demand for improved efficiency underscores the need to enhance these vehicles' navigation capabilities. READ MORE

4. 17. Learning from Interactions : Forward and Inverse Decision-Making for Autonomous Dynamical Systems

   Author : Inês de Miranda de Matos Lourenço; Bo Wahlberg; Sandra Hirche; KTH; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Intelligent systems; autonomous decision-making; Reinforcement Learning; Markov models; Human-Robot Interaction; Biologically-inspired systems; Electrical Engineering; Elektro- och systemteknik;

   Abstract : Decision-making is the mechanism of using available information to generate solutions to given problems by forming preferences, beliefs, and selecting courses of action amongst several alternatives. In this thesis, we study the mechanisms that generate behavior (the forward problem) and how their characteristics can explain observed behavior (the inverse problem). READ MORE

5. 18. Regret Minimization in Structured Reinforcement Learning

   Author : Damianos Tranos; Alexandre Proutiere; Yevgeny Seldin; KTH; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Reinforcement Learning; Electrical Engineering; Elektro- och systemteknik;

   Abstract : We consider a class of sequential decision making problems in the presence of uncertainty, which belongs to the field of Reinforcement Learning (RL). Specifically, we study discrete Markov decision Processes (MDPs) which model a decision maker or agent that interacts with a stochastic and dynamic environment and receives feedback from it in the form of a reward. READ MORE

6. 19. Data-driven personalized healthcare : Towards personalized interventions via reinforcement learning for Mobile Health

   Author : Alexander Galozy; Sławomir Nowaczyk; Mattias Ohlsson; Fredrik Johansson; Högskolan i Halmstad; []
   Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Information Driven Care; Electronic Health Records; Machine Learning; Reinforcement Learning;

   Abstract : Medical and technological advancement in the last century has led to the unprecedented increase of the populace's quality of life and lifespan. As a result, an ever-increasing number of people live with chronic health conditions that require long-term treatment, resulting in increased healthcare costs and managerial burden to the healthcare provider. READ MORE

7. 20. Systematic Data-Driven Continual Self-Learning

   Author : Diarmuid Corcoran; Magnus Boman; Steven Latré; KTH; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Data-Driven Methods; Self-Learning Systems; Reinforcement Learning Algorithms; Implementation Architectures; Datadrivna metoder; Självlärande system; Reinforcement Learning-algoritmer; Implementeringsarkitekturer;

   Abstract : There is a lot of unexploited potential in using data-driven and self-learning methods to dramatically improve automatic decision-making and control in complex industrial systems. So far, and on a relatively small scale, these methods have demonstrated some potential to achieve performance gains for the automated tuning of complex distributed systems. READ MORE