14 citations · 39 across the 10 of their papers we have counts for
3 papers · 1 filter
Neural Lyapunov Control for Discrete-Time Systems
Junlin Wu, Andrew Clark, Yiannis Kantaros +1
While ensuring stability for linear systems is well understood, it remains a major challenge for nonlinear systems. A general approach in such cases is to compute a combination of…
Reinforcement Learning Beyond Expectation
Bhaskar Ramasubramanian, Luyao Niu, Andrew Clark +1
The inputs and preferences of human users are important considerations in situations where these users interact with autonomous cyber or cyber-physical systems. In these scenarios,…
Potential-Based Advice for Stochastic Policy Learning
Baicen Xiao, Bhaskar Ramasubramanian, Andrew Clark +3
This paper augments the reward received by a reinforcement learning agent with potential functions in order to help the agent learn (possibly stochastic) optimal policies. We show…