Mykel Kochenderfer | DeepAI

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∙ 06/03/2022

Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning

Characterizing aleatoric and epistemic uncertainty on the predicted rewa...

0 Bertrand Charpentier, et al. ∙

∙ 03/12/2022

FIG-OP: Exploring Large-Scale Unknown Environments on a Fixed Time Budget

We present a method for autonomous exploration of large-scale unknown en...

0 Oriana Peltzer, et al. ∙

∙ 02/15/2022

A Light-Weight Multi-Objective Asynchronous Hyper-Parameter Optimizer

We describe a light-weight yet performant system for hyper-parameter opt...

11 Gabriel Maher, et al. ∙

∙ 10/17/2021

Coordinated Multi-Agent Pathfinding for Drones and Trucks over Road Networks

We address the problem of routing a team of drones and trucks over large...

9 Shushman Choudhury, et al. ∙

∙ 08/29/2021

A Hybrid Rule-Based and Data-Driven Approach to Driver Modeling through Particle Filtering

Autonomous vehicles need to model the behavior of surrounding human driv...

27 Raunak Bhattacharyya, et al. ∙

∙ 12/24/2020

Hierarchical Planning for Resource Allocation in Emergency Response Systems

A classical problem in city-scale cyber-physical systems (CPS) is resour...

0 Geoffrey Pettet, et al. ∙

∙ 12/03/2020

Obstacle Avoidance Using a Monocular Camera

A collision avoidance system based on simple digital cameras would help ...

0 Kyle Hatch, et al. ∙

∙ 10/30/2020

Handling Missing Data with Graph Representation Learning

Machine learning with missing data has been approached in two different ...

12 Jiaxuan You, et al. ∙

∙ 10/15/2020

Uncertainty Aware Wildfire Management

Recent wildfires in the United States have resulted in loss of life and ...

13 Tina Diao, et al. ∙

∙ 10/15/2020

Designing Emergency Response Pipelines : Lessons and Challenges

Emergency response to incidents such as accidents, crimes, and fires is ...

0 Ayan Mukhopadhyay, et al. ∙

∙ 06/10/2020

Modeling Human Driving Behavior through Generative Adversarial Imitation Learning

Imitation learning is an approach for generating intelligent behavior wh...

0 Raunak Bhattacharyya, et al. ∙

∙ 06/07/2020

A Review of Emergency Incident Prediction, Resource Allocation and Dispatch Models

Emergency response to incidents such as roadway accidents is one of the ...

0 Ayan Mukhopadhyay, et al. ∙

∙ 05/28/2020

Improving Automated Driving through Planning with Human Internal States

This work examines the hypothesis that partially observable Markov decis...

0 Zachary Sunberg, et al. ∙

∙ 05/06/2020

Online Parameter Estimation for Human Driver Behavior Prediction

Driver models are invaluable for planning in autonomous vehicles as well...

0 Raunak Bhattacharyya, et al. ∙

∙ 02/29/2020

Learning Near Optimal Policies with Low Inherent Bellman Error

We study the exploration problem with approximate linear action-value fu...

15 Andrea Zanette, et al. ∙

∙ 01/21/2020

On Algorithmic Decision Procedures in Emergency Response Systems in Smart and Connected Communities

Emergency Response Management (ERM) is a critical problem faced by commu...

0 Geoffrey Pettet, et al. ∙

∙ 12/20/2019

Optimizing Collision Avoidance in Dense Airspace using Deep Reinforcement Learning

New methodologies will be needed to ensure the airspace remains safe and...

17 Sheng Li, et al. ∙

∙ 07/16/2019

Efficient Autonomy Validation in Simulation with Adaptive Stress Testing

During the development of autonomous systems such as driverless cars, it...

2 Mark Koren, et al. ∙

∙ 05/07/2019

Object Exchangeability in Reinforcement Learning: Extended Abstract

Although deep reinforcement learning has advanced significantly over the...

0 John Mern, et al. ∙

∙ 10/22/2018

Learning Probabilistic Trajectory Models of Aircraft in Terminal Airspace from Position Data

Models for predicting aircraft motion are an important component of mode...

0 Shane Barratt, et al. ∙

∙ 02/20/2018

Layer-wise synapse optimization for implementing neural networks on general neuromorphic architectures

Deep artificial neural networks (ANNs) can represent a wide range of com...

0 John Mern, et al. ∙

∙ 01/18/2018

Toward Scalable Verification for Safety-Critical Deep Networks

The increasing use of deep neural networks for safety-critical applicati...

0 Lindsey Kuper, et al. ∙

∙ 09/18/2017

POMCPOW: An online algorithm for POMDPs with continuous state, action, and observation spaces

Online solvers for partially observable Markov decision processes have b...

0 Zachary Sunberg, et al. ∙

∙ 02/03/2017

Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks

Deep neural networks have emerged as a widely used and effective means f...

0 Guy Katz, et al. ∙

∙ 02/02/2017

The Value of Inferring the Internal State of Traffic Participants for Autonomous Freeway Driving

Safe interaction with human drivers is one of the primary challenges for...

0 Zachary Sunberg, et al. ∙

∙ 01/24/2017

Imitating Driver Behavior with Generative Adversarial Networks

The ability to accurately predict and simulate human driving behavior is...

0 Alex Kuefler, et al. ∙

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