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Aditya Mahajan

Researcher at McGill University

Publications -  151
Citations -  2570

Aditya Mahajan is an academic researcher from McGill University. The author has contributed to research in topics: Markov process & Markov chain. The author has an hindex of 24, co-authored 138 publications receiving 2097 citations. Previous affiliations of Aditya Mahajan include University of Michigan & Kyung Hee University.

Papers
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Journal ArticleDOI

Decentralized Stochastic Control with Partial History Sharing: A Common Information Approach

TL;DR: A general model of decentralized stochastic control called partial history sharing information structure is presented and the optimal control problem at the coordinator is shown to be a partially observable Markov decision process (POMDP) which is solved using techniques fromMarkov decision theory.
Book ChapterDOI

Multi-Armed Bandit Problems

TL;DR: The MAB formulation models resource allocation problems arising in several technological and scientific disciplines such as sensor management, manufacturing systems, economics, queueing and communication networks, clinical trials, control theory, search theory, etc.
Proceedings ArticleDOI

Information structures in optimal decentralized control

TL;DR: A comprehensive characterization of information structures in team decision problems and their impact on the tractability of team optimization and norm-optimal control for linear plants under information constraints is provided.
Journal ArticleDOI

Optimal Control Strategies in Delayed Sharing Information Structures

TL;DR: The n-step delayed sharing information structure is investigated and structural results for optimal control strategies for systems with such information structures are presented and a sequential methodology for finding the optimal strategies is derived.
Journal ArticleDOI

A Wireless Soil Moisture Smart Sensor Web Using Physics-Based Optimal Control: Concept and Initial Demonstrations

TL;DR: The overall design of the smart sensor web-including the control architecture, physics-based hydrologic and sensor models, and actuation and communication hardware-is presented and it is shown that the coordinated operation of sensors through the control policy results in substantial savings in resource usage.