8 papers
Provably Efficient Off-Policy Adversarial Imitation Learning with Convergence Guarantees
Yilei Chen, Vittorio Giammarino, James Queeney +1
Adversarial Imitation Learning (AIL) faces challenges with sample inefficiency because of its reliance on sufficient on-policy data to evaluate the performance of the current polic…
Network Epidemic Control via Model Predictive Control: Extended Version
Mahtab Talaei, Alex Olshevsky, Laura F. White +1
Balancing the societal costs of non-pharmaceutical interventions with epidemic suppression requires adaptive feedback control. Rather than relying on state-dependent operational ca…
Multiple-policy Evaluation via Density Estimation
Yilei Chen, Aldo Pacchiano, Ioannis Ch. Paschalidis
We study the multiple-policy evaluation problem where we are given a set of policies and the goal is to evaluate their performance (expected total reward over a fixed horizon)…
A Distributed Optimization Framework to Regulate the Electricity Consumption of a Residential Neighborhood with Renewables
Erhan Can Ozcan, Emiliano Dall'Anese, Ioannis Ch. Paschalidis
Demand response services at the distribution level are emerging as enabling strategies for improving grid reliability in the presence of intermittent renewable generation and grid…
Geometric Re-Analysis of Classical MDP Solving Algorithms
Arsenii Mustafin, Aleksei Pakharev, Alex Olshevsky +1
We build on a recently introduced geometric interpretation of Markov Decision Processes (MDPs) to analyze classical MDP-solving algorithms: Value Iteration (VI) and Policy Iteratio…
MDP Geometry, Normalization and Reward Balancing Solvers
Arsenii Mustafin, Aleksei Pakharev, Alex Olshevsky +1
We present a new geometric interpretation of Markov Decision Processes (MDPs) with a natural normalization procedure that allows us to adjust the value function at each state witho…