44 citations · 364 across the 85 of their papers we have counts for
10 papers · 1 filter
Controlled Information Fusion with Risk-Averse CVaR Social Sensors
Sujay Bhatt, Vikram Krishnamurthy
Consider a multi-agent network comprised of risk averse social sensors and a controller that jointly seek to estimate an unknown state of nature, given noisy measurements. The netw…
A Comprehensive Methodology for Volt-VAR Optimization in Active Smart Grids
Mohammad Ghasemi Damavandi, Vikram Krishnamurthy, Jose R Marti
This paper considers the problem of Volt-VAR Optimization (VVO) in active smart grids. Active smart grids are equipped with distributed generators, distributed storage systems, and…
Partially Observed Markov Decision Processes. Problem Sets and Internet Supplement
Vikram Krishnamurthy
This document is an internet supplement to my book "Partially Observed Markov Decision Processes - From Filtering to Controlled Sensing" published by Cambridge University Press in…
Structural Results for Partially Observed Markov Decision Processes
Vikram Krishnamurthy
This article provides an introductory tutorial on structural results in partially observed Markov decision processes (POMDPs). Typically, computing the optimal policy of a POMDP is…
Sequential Detection of Market shocks using Risk-averse Agent Based Models
Vikram Krishnamurthy, Sujay Bhatt
This paper considers a statistical signal processing problem involving agent based models of financial markets which at a micro-level are driven by socially aware and risk- averse…
Myopic Bounds for Optimal Policy of POMDPs: An extension of Lovejoy's structural results
Vikram Krishnamurthy, Udit Pareek
This paper provides a relaxation of the sufficient conditions, and also an extension of the structural results for Partially Observed Markov Decision Processes (POMDPs) given in Lo…
Adaptive Search Algorithms for Discrete Stochastic Optimization: A Smooth Best-Response Approach
Omid Namvar Gharehshiran, Vikram Krishnamurthy, George Yin
This paper considers simulation-based optimization of the performance of a regime-switching stochastic system over a finite set of feasible configurations. Inspired by the stochast…
When to look at a noisy Markov chain in sequential decision making if measurements are costly?
Vikram Krishnamurthy
A decision maker records measurements of a finite-state Markov chain corrupted by noise. The goal is to decide when the Markov chain hits a specific target state. The decision make…
Sequential Detection with Mutual Information Stopping Cost
Vikram Krishnamurthy, Robert Bitmead, Michel Gevers +1
This paper formulates and solves a sequential detection problem that involves the mutual information (stochastic observability) of a Gaussian process observed in noise with missing…
Real-Time Reinforcement Learning of Constrained Markov Decision Processes with Weak Derivatives
Vikram Krishnamurthy, Felisa Vazquez Abad
We present on-line policy gradient algorithms for computing the locally optimal policy of a constrained, average cost, finite state Markov Decision Process. The stochastic approxim…