12 citations · 15 across the 17 of their papers we have counts for
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Safe Learning of Adaptive Control Policies for Remote Patient Monitoring
Ramanan Tamizholi, Siddharth Chandak, Isha Thapa +2
Remote Patient Monitoring (RPM) enables continuous observation of patients in their daily environments, improving both health outcomes and quality of life. A key challenge in RPM i…
Optimal Control for Remote Patient Monitoring with Multidimensional Health States
Siddharth Chandak, Isha Thapa, Nicholas Bambos +1
Selecting the right monitoring level in Remote Patient Monitoring (RPM) systems for e-healthcare is crucial for balancing patient outcomes, various resources, and patient's quality…
Tiered Service Architecture for Remote Patient Monitoring
Siddharth Chandak, Isha Thapa, Nicholas Bambos +1
We develop a remote patient monitoring (RPM) service architecture, which has two tiers of monitoring: ordinary and intensive. The patient's health state improves or worsens in each…
Reinforcement Learning in Non-Markovian Environments
Siddharth Chandak, Pratik Shah, Vivek S Borkar +1
Motivated by the novel paradigm developed by Van Roy and coauthors for reinforcement learning in arbitrary non-Markovian environments, we propose a related formulation and explicit…
Prospect-theoretic Q-learning
Vivek S. Borkar, Siddharth Chandak
We consider a prospect theoretic version of the classical Q-learning algorithm for discounted reward Markov decision processes, wherein the controller perceives a distorted and noi…