6 citations · 6 across the 6 of their papers we have counts for
8 papers · 1 filter
Entropy-Regularized Partially Observed Markov Decision Processes
Timothy L. Molloy, Girish N. Nair
We investigate partially observed Markov decision processes (POMDPs) with cost functions regularized by entropy terms describing state, observation, and control uncertainty. Standa…
Smoother Entropy for Active State Trajectory Estimation and Obfuscation in POMDPs
Timothy L. Molloy, Girish N. Nair
We study the problem of controlling a partially observed Markov decision process (POMDP) to either aid or hinder the estimation of its state trajectory. We encode the estimation ob…
Granger Causality from Quantized Measurements
Salman Ahmadi, Girish N. Nair, Erik Weyer
An approach is proposed for inferring Granger causality between jointly stationary, Gaussian signals from quantized data. First, a necessary and sufficient rank criterion for the e…
Active Trajectory Estimation for Partially Observed Markov Decision Processes via Conditional Entropy
Timothy L. Molloy, Girish N. Nair
In this paper, we consider the problem of controlling a partially observed Markov decision process (POMDP) in order to actively estimate its state trajectory over a fixed horizon w…
Smoothing-Averse Control: Covertness and Privacy from Smoothers
Timothy L. Molloy, Girish N. Nair
In this paper we investigate the problem of controlling a partially observed stochastic dynamical system such that its state is difficult to infer using a (fixed-interval) Bayesian…
Bounded State Estimation over Finite-State Channels: Relating Topological Entropy and Zero-Error Capacity
Amir Saberi, Farhad Farokhi, Girish N. Nair
We investigate state estimation of linear systems over channels having a finite state not known by the transmitter or receiver. We show that similar to memoryless channels, zero-er…