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Found 4 papers, 1 papers with code
Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off
A default assumption in reinforcement learning (RL) and optimal control is that observations arrive at discrete time points on a fixed clock cycle.
To Compute or not to Compute? Adaptive Smart Sensing in Resource-Constrained Edge Computing
We consider a network of smart sensors for an edge computing application that sample a time-varying signal and send updates to a base station for remote global monitoring.
A Reinforcement Learning Approach to Sensing Design in Resource-Constrained Wireless Networked Control Systems
In this paper, we consider a wireless network of smart sensors (agents) that monitor a dynamical process and send measurements to a base station that performs global monitoring and decision-making.
Estimating Koopman operators for nonlinear dynamical systems: a nonparametric approach
The Koopman operator is a mathematical tool that allows for a linear description of non-linear systems, but working in infinite dimensional spaces.
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