4 papers
A Control Theory inspired Exploration Method for a Linear Bandit driven by a Linear Gaussian Dynamical System
Jonathan Gornet, Yilin Mo, Bruno Sinopoli
The paper introduces a linear bandit environment where the reward is the output of a known Linear Gaussian Dynamical System (LGDS). In this environment, we address the fundamental…
HyperController: A Hyperparameter Controller for Fast and Stable Training of Reinforcement Learning Neural Networks
Jonathan Gornet, Yiannis Kantaros, Bruno Sinopoli
We introduce Hyperparameter Controller (HyperController), a computationally efficient algorithm for hyperparameter optimization during training of reinforcement learning neural net…
An Exploration-free Method for a Linear Stochastic Bandit Driven by a Linear Gaussian Dynamical System
Jonathan Gornet, Yilin Mo, Bruno Sinopoli
In stochastic multi-armed bandits, a major problem the learner faces is the trade-off between exploration and exploitation. Recently, exploration-free methods -- methods that commi…
Stochastic Multi-armed Bandits with Non-stationary Rewards Generated by a Linear Dynamical System
Jonathan Gornet, Mehdi Hosseinzadeh, Bruno Sinopoli
The stochastic multi-armed bandit has provided a framework for studying decision-making in unknown environments. We propose a variant of the stochastic multi-armed bandit where the…