8 citations · 20 across the 10 of their papers we have counts for
12 papers
Active Reward Machine Inference From Raw State Trajectories
Mohamad Louai Shehab, Antoine Aspeel, Necmiye Ozay
Reward machines are automaton-like structures that capture the memory required to accomplish a multi-stage task. When combined with reinforcement learning or optimal control method…
Exploiting Over-Approximation Errors as Preview Information for Nonlinear Control
Antoine Aspeel, Antoine Girard, Thiago Alves Lima
We study the control of nonlinear constrained systems via over-approximations. Our key observation is that the over-approximation error, rather than being an unknown disturbance, c…
Mode-Prefix-Based Control of Switched Linear Systems with Applications to Fault Tolerance
Ram Padmanabhan, Antoine Aspeel, Necmiye Ozay +1
In this paper, we consider the problem of designing prefix-based optimal controllers for switched linear systems over finite horizons. This problem arises in fault-tolerant control…
Learning Reward Machines from Partially Observed Policies
Mohamad Louai Shehab, Antoine Aspeel, Necmiye Ozay
Inverse reinforcement learning is the problem of inferring a reward function from an optimal policy or demonstrations by an expert. In this work, it is assumed that the reward is e…
Minimal L2-Consistent Data-Transmission
Antoine Aspeel, Laurent Bako, Necmiye Ozay
In this work, we consider non-collocated sensors and actuators, and we address the problem of minimizing the number of sensor-to-actuator transmissions while ensuring that the L2 g…
A Simulation Preorder for Koopman-like Lifted Control Systems
Antoine Aspeel, Necmiye Ozay
This paper introduces a simulation preorder among lifted systems, a generalization of finite-dimensional Koopman approximations (also known as approximate immersions) to systems wi…
A Low Rank Approach to Minimize Sensor-to-Actuator Communication in Finite Horizon Output Feedback
Antoine Aspeel, Jakob Nylof, Jing Shuang Li +1
Many modern controllers are composed of different components that communicate in real-time over some network with limited resources. In this work, we are interested in designing a…
Koopman-inspired Implicit Backward Reachable Sets for Unknown Nonlinear Systems
Haldun Balim, Antoine Aspeel, Zexiang Liu +1
Koopman liftings have been successfully used to learn high dimensional linear approximations for autonomous systems for prediction purposes, or for control systems for leveraging l…
Optimal Intermittent Particle Filter
Antoine Aspeel, Amaury Gouverneur, Raphaël M. Jungers +1
The problem of the optimal allocation (in the expected mean square error sense) of a measurement budget for particle filtering is addressed. We propose three different optimal inte…
Optimal Control for Linear Networked Control Systems with Information Transmission Constraints
Antoine Aspeel, Kwesi Rutledge, Raphaël M. Jungers +2
This paper addresses the problem of robust control of a linear discrete-time system subject to bounded disturbances and to measurement and control budget constraints. Using Q-param…
Optimal measurement budget allocation for particle filtering
Antoine Aspeel, Amaury Gouverneur, Raphaël M. Jungers +1
Particle filtering is a powerful tool for target tracking. When the budget for observations is restricted, it is necessary to reduce the measurements to a limited amount of samples…
Optimal Intermittent Measurements for Tumor Tracking in X-ray Guided Radiotherapy
Antoine Aspeel, Damien Dasnoy, Raphaël M. Jungers +1
In radiation therapy, tumor tracking is a challenging task that allows a better dose delivery. One practice is to acquire X-ray images in real-time during treatment, that are used…