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Reinforcement learning for intelligent healthcare applications: A survey
A Coronato, M Naeem, G De Pietro… - Artificial intelligence in …, 2020 - Elsevier
Discovering new treatments and personalizing existing ones is one of the major goals of
modern clinical research. In the last decade, Artificial Intelligence (AI) has enabled the …
modern clinical research. In the last decade, Artificial Intelligence (AI) has enabled the …
A tutorial on partially observable Markov decision processes
ML Littman - Journal of Mathematical Psychology, 2009 - Elsevier
The partially observable Markov decision process (POMDP) model of environments was first
explored in the engineering and operations research communities 40 years ago. More …
explored in the engineering and operations research communities 40 years ago. More …
Perseus: Randomized point-based value iteration for POMDPs
Partially observable Markov decision processes (POMDPs) form an attractive and principled
framework for agent planning under uncertainty. Point-based approximate techniques for …
framework for agent planning under uncertainty. Point-based approximate techniques for …
Partially observable Markov decision processes
MTJ Spaan - Reinforcement learning: State-of-the-art, 2012 - Springer
For reinforcement learning in environments in which an agent has access to a reliable state
signal, methods based on the Markov decision process (MDP) have had many successes. In …
signal, methods based on the Markov decision process (MDP) have had many successes. In …
The COACH prompting system to assist older adults with dementia through handwashing: An efficacy study
A Mihailidis, JN Boger, T Craig, J Hoey - BMC geriatrics, 2008 - Springer
Background Many older adults with dementia require constant assistance from a caregiver
when completing activities of daily living (ADL). This study examines the efficacy of a …
when completing activities of daily living (ADL). This study examines the efficacy of a …
An analytic solution to discrete Bayesian reinforcement learning
Reinforcement learning (RL) was originally proposed as a framework to allow agents to
learn in an online fashion as they interact with their environment. Existing RL algorithms …
learn in an online fashion as they interact with their environment. Existing RL algorithms …
Ontology‐based activity recognition in intelligent pervasive environments
Purpose–This paper aims to serve two main purposes. In the first instance it aims to it
provide an overview addressing the state‐of‐the‐art in the area of activity recognition, in …
provide an overview addressing the state‐of‐the‐art in the area of activity recognition, in …
Automated handwashing assistance for persons with dementia using video and a partially observable Markov decision process
This paper presents a real-time vision-based system to assist a person with dementia wash
their hands. The system uses only video inputs, and assistance is given as either verbal or …
their hands. The system uses only video inputs, and assistance is given as either verbal or …
[PDF][PDF] Point-based value iteration for continuous POMDPs
We propose a novel approach to optimize Partially Observable Markov Decisions Processes
(POMDPs) defined on continuous spaces. To date, most algorithms for model-based …
(POMDPs) defined on continuous spaces. To date, most algorithms for model-based …
[ספר][B] Exploiting structure to efficiently solve large scale partially observable Markov decision processes
P Poupart - 2005 - Citeseer
Partially observable Markov decision processes (POMDPs) provide a natural and principled
framework to model a wide range of sequential decision making problems under …
framework to model a wide range of sequential decision making problems under …