44 citations · 364 across the 85 of their papers we have counts for
11 papers · 1 filter
Dynamics of Social Networks: Multi-agent Information Fusion, Anticipatory Decision Making and Polling
Vikram Krishnamurthy
This paper surveys mathematical models, structural results and algorithms in controlled sensing with social learning in social networks. Part 1, namely Bayesian Social Learning wit…
How can a Radar Mask its Cognition?
Kunal Pattanayak, Vikram Krishnamurthy, Christopher Berry
A cognitive radar is a constrained utility maximizer that adapts its sensing mode in response to a changing environment. If an adversary can estimate the utility function of a cogn…
Adaptive Filtering Algorithms for Set-Valued Observations -- Symmetric Measurement Approach to Unlabeled and Anonymized Data
Vikram Krishnamurthy
Suppose simultaneous independent stochastic systems generate observations, where the observations from each system depend on the underlying parameter of that system. The observ…
Quickest Detection for Human-Sensor Systems using Quantum Decision Theory
Luke Snow, Vikram Krishnamurthy, Brian M. Sadler
In mathematical psychology, recent models for human decision-making use Quantum Decision Theory to capture important human-centric features such as order effects and violation of t…
Meta-Cognition. An Inverse-Inverse Reinforcement Learning Approach for Cognitive Radars
Kunal Pattanayak, Vikram Krishnamurthy, Christopher Berry
This paper considers meta-cognitive radars in an adversarial setting. A cognitive radar optimally adapts its waveform (response) in response to maneuvers (probes) of a possibly adv…
How can a Cognitive Radar Mask its Cognition?
Kunal Pattanayak, Vikram Krishnamurthy, Christopher Berry
We study how a cognitive radar can mask (hide) its cognitive ability from an adversarial jamming device. Specifically, if the radar optimally adapts its waveform based on adversari…
Principal Agent Problem as a Principled Approach to Electronic Counter-Countermeasures in Radar
Anurag Gupta, Vikram Krishnamurthy
Electronic countermeasures (ECM) against a radar are actions taken by an adversarial jammer to mitigate effective utilization of the electromagnetic spectrum by the radar. On the o…
Adversarial Radar Inference: Inverse Tracking, Identifying Cognition and Designing Smart Interference
Vikram Krishnamurthy, Kunal Pattanayak, Sandeep Gogineni +2
This paper considers three inter-related adversarial inference problems involving cognitive radars. We first discuss inverse tracking of the radar to estimate the adversary's estim…
Adversarial Radar Inference. From Inverse Tracking to Inverse Reinforcement Learning of Cognitive Radar
Vikram Krishnamurthy
Cognitive sensing refers to a reconfigurable sensor that dynamically adapts its sensing mechanism by using stochastic control to optimize its sensing resources. For example, cognit…
Identifying Cognitive Radars -- Inverse Reinforcement Learning using Revealed Preferences
Vikram Krishnamurthy, Daniel Angley, Robin Evans +1
We consider an inverse reinforcement learning problem involving us versus an enemy radar equipped with a Bayesian tracker. By observing the emissions of the enemy radar,how can we…
How to Calibrate your Adversary's Capabilities? Inverse Filtering for Counter-Autonomous Systems
Vikram Krishnamurthy, Muralidhar Rangaswamy
We consider an adversarial Bayesian signal processing problem involving "us" and an "adversary". The adversary observes our state in noise; updates its posterior distribution of th…