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Control of Agreement and Disagreement Cascades with Distributed Inputs
For a group of autonomous communicating agents, the ability to distingui...
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Distributed Bandits: Probabilistic Communication on d-regular Graphs
We study the decentralized multi-agent multi-armed bandit problem for ag...
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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...
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LagNetViP: A Lagrangian Neural Network for Video Prediction
The dominant paradigms for video prediction rely on opaque transition mo...
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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...
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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...
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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...
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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 ...
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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 ...
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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 ...
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Satisficing in multi-armed bandit problems
Satisficing is a relaxation of maximizing and allows for less risky deci...
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On Distributed Cooperative Decision-Making in Multiarmed Bandits
We study the explore-exploit tradeoff in distributed cooperative decisio...
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Correlated Multiarmed Bandit Problem: Bayesian Algorithms and Regret Analysis
We consider the correlated multiarmed bandit (MAB) problem in which the ...
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