Naomi Ehrich Leonard

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Professor of Mechanical and Aerospace Engineering at Princeton University, Edwin S. Wilsey Professor of Mechanical and Aerospace Engineering at Princeton University, Director of the Princeton Council on Science and Technology and an associated faculty member in the Program in Applied & Computational Mathematics, Princeton Neuroscience Institute, and the Program in Quantitative and Computational Biology.

Featured Co-authors

Anirudha Majumdar
19 publications
Amit Chakraborty
13 publications
Vaibhav Srivastava
12 publications
Biswadip Dey
8 publications
Udari Madhushani
6 publications
Yaofeng Desmond Zhong
6 publications
Christine Allen-Blanchette
5 publications
Sushant Veer
5 publications
Paul Reverdy
4 publications
Peter Landgren
2 publications
Anastasia Bizyaeva
1 publication

Control of Agreement and Disagreement Cascades with Distributed Inputs

For a group of autonomous communicating agents, the ability to distingui...
03/26/2021 ∙ by Anastasia Bizyaeva, et al. ∙ 0 ∙ share

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Distributed Bandits: Probabilistic Communication on d-regular Graphs

We study the decentralized multi-agent multi-armed bandit problem for ag...
11/16/2020 ∙ by Udari Madhushani, et al. ∙ 1 ∙ share

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Hamiltonian Q-Learning: Leveraging Importance-sampling for Data Efficient RL

Model-free reinforcement learning (RL), in particular Q-learning is wide...
11/11/2020 ∙ by Udari Madhushani, et al. ∙ 7 ∙ share

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LagNetViP: A Lagrangian Neural Network for Video Prediction

The dominant paradigms for video prediction rely on opaque transition mo...
10/24/2020 ∙ by Christine Allen-Blanchette, et al. ∙ 9 ∙ share

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Influence Spread in the Heterogeneous Multiplex Linear Threshold Model

The linear threshold model (LTM) has been used to study spread on single...
08/10/2020 ∙ by Yaofeng Desmond Zhong, et al. ∙ 0 ∙ share

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Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control

Recent approaches for modelling dynamics of physical systems with neural...
07/03/2020 ∙ by Yaofeng Desmond Zhong, et al. ∙ 0 ∙ share

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Distributed Learning: Sequential Decision Making in Resource-Constrained Environments

We study cost-effective communication strategies that can be used to imp...
04/13/2020 ∙ by Udari Madhushani, et al. ∙ 8 ∙ share

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A Dynamic Observation Strategy for Multi-agent Multi-armed Bandit Problem

We define and analyze a multi-agent multi-armed bandit problem in which ...
04/08/2020 ∙ by Udari Madhushani, et al. ∙ 0 ∙ share

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Distributed Cooperative Decision Making in Multi-agent Multi-armed Bandits

We study a distributed decision-making problem in which multiple agents ...
03/03/2020 ∙ by Peter Landgren, et al. ∙ 0 ∙ share

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Heterogeneous Stochastic Interactions for Multiple Agents in a Multi-armed Bandit Problem

We define and analyze a multi-agent multi-armed bandit problem in which ...
05/21/2019 ∙ by Udari Madhushani, et al. ∙ 0 ∙ share

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Satisficing in multi-armed bandit problems

Satisficing is a relaxation of maximizing and allows for less risky deci...
12/23/2015 ∙ by Paul Reverdy, et al. ∙ 0 ∙ share

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On Distributed Cooperative Decision-Making in Multiarmed Bandits

We study the explore-exploit tradeoff in distributed cooperative decisio...
12/21/2015 ∙ by Peter Landgren, et al. ∙ 0 ∙ share

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Correlated Multiarmed Bandit Problem: Bayesian Algorithms and Regret Analysis

We consider the correlated multiarmed bandit (MAB) problem in which the ...
07/05/2015 ∙ by Vaibhav Srivastava, et al. ∙ 0 ∙ share

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