7 citations · 11 across the 10 of their papers we have counts for
10 papers
Adaptive ECCM for Mitigating Smart Jammers
Kunal Pattanayak, Shashwat Jain, Vikram Krishnamurthy +1
This paper considers adaptive radar electronic counter-counter measures (ECCM) to mitigate ECM by an adversarial jammer. Our ECCM approach models the jammer-radar interaction as a…
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…
Inverse-Inverse Reinforcement Learning. How to Hide Strategy from an Adversarial Inverse Reinforcement Learner
Kunal Pattanayak, Vikram Krishnamurthy, Christopher Berry
Inverse reinforcement learning (IRL) deals with estimating an agent's utility function from its actions. In this paper, we consider how an agent can hide its strategy and mitigate…
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…
Unifying Revealed Preference and Revealed Rational Inattention
Kunal Pattanayak, Vikram Krishnamurthy
This paper unifies two key results from economic theory, namely, revealed rational inattention and classical revealed preference. Revealed rational inattention tests for rationalit…
Rationally Inattentive Utility Maximization for Interpretable Deep Image Classification
Kunal Pattanayak, Vikram Krishnamurthy
Are deep convolutional neural networks (CNNs) for image classification explainable by utility maximization with information acquisition costs? We demonstrate that deep CNNs behave…
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…
Necessary and Sufficient Conditions for Inverse Reinforcement Learning of Bayesian Stopping Time Problems
Kunal Pattanayak, Vikram Krishnamurthy
This paper presents an inverse reinforcement learning~(IRL) framework for Bayesian stopping time problems. By observing the actions of a Bayesian decision maker, we provide a neces…
Rationally Inattentive Inverse Reinforcement Learning Explains YouTube Commenting Behavior
William Hoiles, Vikram Krishnamurthy, Kunal Pattanayak
We consider a novel application of inverse reinforcement learning with behavioral economics constraints to model, learn and predict the commenting behavior of YouTube viewers. Each…