44 citations · 364 across the 85 of their papers we have counts for
12 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…
Estimating Exposure to Information on Social Networks
Buddhika Nettasinghe, Kowe Kadoma, Mor Naaman +1
This paper considers the problem of estimating exposure to information in a social network. Given a piece of information (e.g., a URL of a news article on Facebook, a hashtag on Tw…
Lyapunov based Stochastic Stability of a Quantum Decision System for Human-Machine Interaction
Luke Snow, Shashwat Jain, Vikram Krishnamurthy
In mathematical psychology, decision makers are modeled using the Lindbladian equations from quantum mechanics to capture important human-centric features such as order effects and…
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…
Lyapunov based Stochastic Stability of Human-Machine Interaction: A Quantum Decision System Approach
Luke Snow, Shashwat Jain, Vikram Krishnamurthy
In mathematical psychology, decision makers are modeled using the Lindbladian equations from quantum mechanics to capture important human-centric features such as order effects and…
Hawkes Process Modeling of Block Arrivals in Bitcoin Blockchain
Rui Luo, Vikram Krishnamurthy, Erik Blasch
The paper constructs a multi-variate Hawkes process model of Bitcoin block arrivals and price jumps. Hawkes processes are selfexciting point processes that can capture the self- an…
Interval Dominance based Structural Results for Markov Decision Process
Vikram Krishnamurthy
Structural results impose sufficient conditions on the model parameters of a Markov decision process (MDP) so that the optimal policy is an increasing function of the underlying st…
Controlling Transaction Rate in Tangle Ledger: A Principal Agent Problem Approach
Anurag Gupta, Vikram Krishnamurthy
Tangle is a distributed ledger technology that stores data as a directed acyclic graph (DAG). Unlike blockchain, Tangle does not require dedicated miners for its operation; this ma…