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The Computation of Approximate Generalized Feedback Nash Equilibria
We present the concept of a Generalized Feedback Nash Equilibrium (GFNE)...
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Multi-Hypothesis Interactions in Game-Theoretic Motion Planning
We present a novel method for handling uncertainty about the intentions ...
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Testing for Typicality with Respect to an Ensemble of Learned Distributions
Methods of performing anomaly detection on high-dimensional data sets ar...
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DeepReach: A Deep Learning Approach to High-Dimensional Reachability
Hamilton-Jacobi (HJ) reachability analysis is an important formal verifi...
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Expert Selection in High-Dimensional Markov Decision Processes
In this work we present a multi-armed bandit framework for online expert...
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Feature Expansive Reward Learning: Rethinking Human Input
In collaborative human-robot scenarios, when a person is not satisfied w...
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Visual Navigation Among Humans with Optimal Control as a Supervisor
Real world navigation requires robots to operate in unfamiliar, dynamic ...
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Generating Robust Supervision for Learning-Based Visual Navigation Using Hamilton-Jacobi Reachability
In Bansal et al. (2019), a novel visual navigation framework that combin...
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Design of the First Insect-scale Spinning-wing Robot
Here we present the design of an insect-scale microrobot that generates ...
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New Wing Stroke and Wing Pitch Approaches for Milligram-scale Aerial Devices
Here we report the construction of the simplest transmission mechanism e...
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Design of the first sub-milligram flapping wing aerial vehicle
Here we report the first sub-milligram flapping wing vehicle which is ab...
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An Insect-scale Self-sufficient Rolling Microrobot
We design an insect-sized rolling microrobot driven by continuously rota...
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An Insect-scale Untethered Laser-powered Jumping Microrobot
We present the design of an insect-sized jumping microrobot measuring 17...
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Combining Optimal Control and Learning for Visual Navigation in Novel Environments
Model-based control is a popular paradigm for robot navigation because i...
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Regression-based Inverter Control for Decentralized Optimal Power Flow and Voltage Regulation
Electronic power inverters are capable of quickly delivering reactive po...
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Fast Neural Network Verification via Shadow Prices
To use neural networks in safety-critical settings it is paramount to pr...
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A Successive-Elimination Approach to Adaptive Robotic Sensing
We study the adaptive sensing problem for the multiple source seeking pr...
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The Parallelization of Riccati Recursion
A method is presented for parallelizing the computation of solutions to ...
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Customized Local Differential Privacy for Multi-Agent Distributed Optimization
Real-time data-driven optimization and control problems over networks ma...
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Data-Driven Decentralized Optimal Power Flow
The implementation of optimal power flow (OPF) methods to perform voltag...
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A Sequential Approximation Framework for Coded Distributed Optimization
Building on the previous work of Lee et al. and Ferdinand et al. on code...
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MBMF: Model-Based Priors for Model-Free Reinforcement Learning
Reinforcement Learning is divided in two main paradigms: model-free and ...
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Fully Decentralized Policies for Multi-Agent Systems: An Information Theoretic Approach
Learning cooperative policies for multi-agent systems is often challenge...
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