activity
20182022
most citedOptimal communication and control strategies in a multi-agent MDP problem

3 citations · 3 across the 4 of their papers we have counts for

collaborators

10 papers

eess.SY2022

Optimal Communication and Control Strategies for a Multi-Agent System in the Presence of an Adversary

Dhruva Kartik, Sagar Sudhakara, Rahul Jain +1

We consider a multi-agent system in which a decentralized team of agents controls a stochastic system in the presence of an adversary. Instead of committing to a fixed information…

eess.SY2022

Optimal Control of Partially Observable Markov Decision Processes with Finite Linear Temporal Logic Constraints

Krishna C. Kalagarla, Dhruva Kartik, Dongming Shen +3

Autonomous agents often operate in scenarios where the state is partially observed. In addition to maximizing their cumulative reward, agents must execute complex tasks with rich t…

math.OC20213 cited

Optimal communication and control strategies in a multi-agent MDP problem

Sagar Sudhakara, Dhruva Kartik, Rahul Jain +1

The problem of controlling multi-agent systems under different models of information sharing among agents has received significant attention in the recent literature. In this paper…

cs.MA2021

Common Information Belief based Dynamic Programs for Stochastic Zero-sum Games with Competing Teams

Dhruva Kartik, Ashutosh Nayyar, Urbashi Mitra

Decentralized team problems where players have asymmetric information about the state of the underlying stochastic system have been actively studied, but \emph{games} between such…

stat.ME2020

Adaptive Sampling for Estimating Distributions: A Bayesian Upper Confidence Bound Approach

Dhruva Kartik, Neeraj Sood, Urbashi Mitra +1

The problem of adaptive sampling for estimating probability mass functions (pmf) uniformly well is considered. Performance of the sampling strategy is measured in terms of the wors…

cs.IT2020

Testing for Anomalies: Active Strategies and Non-asymptotic Analysis

Dhruva Kartik, Ashutosh Nayyar, Urbashi Mitra

The problem of verifying whether a multi-component system has anomalies or not is addressed. Each component can be probed over time in a data-driven manner to obtain noisy observat…