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Found 10 papers, 2 papers with code
Data-driven architecture to encode information in the kinematics of robots and artificial avatars
We present a data-driven control architecture for modifying the kinematics of robots and artificial avatars to encode specific information such as the presence or not of an emotion in the movements of an avatar or robot driven by a human operator.
In vivo learning-based control of microbial populations density in bioreactors
Our work showcases the viability of learning-based strategies for the control of cellular density in bioreactors, making a step forward toward their use for the control of the composition of microbial consortia.
Guaranteeing Control Requirements via Reward Shaping in Reinforcement Learning
In addressing control problems such as regulation and tracking through reinforcement learning, it is often required to guarantee that the acquired policy meets essential performance and stability criteria such as a desired settling time and steady-state error prior to deployment.
CT-DQN: Control-Tutored Deep Reinforcement Learning
One of the major challenges in Deep Reinforcement Learning for control is the need for extensive training to learn the policy.
External control of a genetic toggle switch via Reinforcement Learning
We investigate the problem of using a learning-based strategy to stabilize a synthetic toggle switch via an external control approach.
Intermittent non-pharmaceutical strategies to mitigate the COVID-19 epidemic in a network model of Italy via constrained optimization
This paper is concerned with the design of intermittent non-pharmaceutical strategies to mitigate the spread of the COVID-19 epidemic exploiting network epidemiological models.
Tutoring Reinforcement Learning via Feedback Control
We introduce a control-tutored reinforcement learning (CTRL) algorithm.
Intermittent yet coordinated regional strategies can alleviate the COVID-19 epidemic: a network model of the Italian case
Using the model, we confirm the effectiveness at the regional level of the national lockdown strategy implemented so far by the Italian government to mitigate the spread of the disease and show its efficacy at the regional level.
Physics and Society Populations and Evolution 93C10, 92D30, 92D25 J.2
Control-Tutored Reinforcement Learning
We introduce a control-tutored reinforcement learning (CTRL) algorithm.
Control-Tutored Reinforcement Learning: an application to the Herding Problem
In this extended abstract we introduce a novel control-tutored Q-learning approach (CTQL) as part of the ongoing effort in developing model-based and safe RL for continuous state spaces.
