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ORCIDMykel J. Kochenderfer
Mykel John Kochenderfer
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- affiliation: Stanford University
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2020 – today
- 2022
[j29]Shushman Choudhury
, Jayesh K. Gupta, Mykel J. Kochenderfer, Dorsa Sadigh, Jeannette Bohg:
Dynamic multi-robot task allocation under uncertainty and temporal constraints. Auton. Robots 46(1): 231-247 (2022)- [j28]Shushman Choudhury, Jayesh K. Gupta, Peter Morales, Mykel J. Kochenderfer:
Scalable Online Planning for Multi-Agent MDPs. J. Artif. Intell. Res. 73: 821-846 (2022) - [c138]Soyeon Jung, Ransalu Senanayake, Mykel J. Kochenderfer:
A Gray Box Model for Characterizing Driver Behavior. SafeAI@AAAI 2022 - [c137]Xiaobai Ma, David Isele, Jayesh K. Gupta, Kikuo Fujimura, Mykel J. Kochenderfer:
Recursive Reasoning Graph for Multi-Agent Reinforcement Learning. AAAI 2022: 7664-7671 - [c136]John Mern, Sidhart Krishnan, Anil Yildiz, Kyle Hatch, Mykel J. Kochenderfer:
Interpretable Local Tree Surrogate Policies. SafeAI@AAAI 2022 - [c135]Ann-Katrin Reuel, Mark Koren, Anthony Corso, Mykel J. Kochenderfer:
Using Adaptive Stress Testing to Identify Paths to Ethical Dilemmas in Autonomous Systems. SafeAI@AAAI 2022 - [c134]Shushman Choudhury, Kiril Solovey, Mykel J. Kochenderfer, Marco Pavone:
Coordinated Multi-Agent Pathfinding for Drones and Trucks over Road Networks. AAMAS 2022: 272-280 - [c133]Jennifer She, Jayesh K. Gupta, Mykel J. Kochenderfer:
Agent-Time Attention for Sparse Rewards Multi-Agent Reinforcement Learning. AAMAS 2022: 1723-1725 - [c132]John Mern, Kyle Hatch, Ryan Silva, Cameron Hickert, Tamim Sookoor, Mykel J. Kochenderfer:
Autonomous Attack Mitigation for Industrial Control Systems. DSN Workshops 2022: 28-36 - [c131]Masha Itkina, Ye-Ji Mun, Katherine Driggs Campbell, Mykel J. Kochenderfer:
Multi-Agent Variational Occlusion Inference Using People as Sensors. ICRA 2022: 4585-4591 - [c130]Sheng Li, Yutai Zhou, Ross E. Allen, Mykel J. Kochenderfer:
Learning Emergent Discrete Message Communication for Cooperative Reinforcement Learning. ICRA 2022: 5511-5517 - [c129]Victoria Magdalena Dax, Mykel J. Kochenderfer, Ransalu Senanayake, Umair Ibrahim:
Infrastructure-Enabled Autonomy: An Attention Mechanism for Occlusion Handling. ICRA 2022: 5939-5945 - [c128]Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer:
Scalable Anytime Planning for Multi-Agent MDPs (Extended Abstract). IJCAI 2022: 5279-5283 - [c127]Samuel Low, Mykel J. Kochenderfer:
Optimal Pointing Sequences in Spacecraft Formation Flying Using Online Planning with Resource Constraints. L4DC 2022: 355-365 - [c126]Christopher A. Strong, Sydney M. Katz, Anthony L. Corso, Mykel J. Kochenderfer:
ZoPE: A Fast Optimizer for ReLU Networks with Low-Dimensional Inputs. NFM 2022: 299-317 - [e1]Roya Firoozi, Negar Mehr, Esen Yel, Rika Antonova, Jeannette Bohg, Mac Schwager, Mykel J. Kochenderfer:
Learning for Dynamics and Control Conference, L4DC 2022, 23-24 June 2022, Stanford University, Stanford, CA, USA. Proceedings of Machine Learning Research 168, PMLR 2022 [contents] - [i156]Arec L. Jamgochian, Kunal Menda, Mykel J. Kochenderfer:
Multi-Vehicle Control in Roundabouts using Decentralized Game-Theoretic Planning. CoRR abs/2201.02718 (2022) - [i155]Arec L. Jamgochian, Di Wu, Kunal Menda, Soyeon Jung, Mykel J. Kochenderfer:
Conditional Approximate Normalizing Flows for Joint Multi-Step Probabilistic Forecasting with Application to Electricity Demand. CoRR abs/2201.02753 (2022) - [i154]Chelsea Sidrane, Sydney M. Katz, Anthony Corso, Mykel J. Kochenderfer:
Verifying Inverse Model Neural Networks. CoRR abs/2202.02429 (2022) - [i153]Gabriel Maher, Stephen P. Boyd, Mykel John Kochenderfer, Cristian Matache, Alex Ulitsky, Slava Yukhymuk, Leonid Kopman:
A Light-Weight Multi-Objective Asynchronous Hyper-Parameter Optimizer. CoRR abs/2202.07735 (2022) - [i152]Xiaobai Ma, David Isele, Jayesh K. Gupta, Kikuo Fujimura, Mykel J. Kochenderfer:
Recursive Reasoning Graph for Multi-Agent Reinforcement Learning. CoRR abs/2203.02844 (2022) - [i151]Christopher Lazarus, Mykel J. Kochenderfer:
Deep Binary Reinforcement Learning for Scalable Verification. CoRR abs/2203.05704 (2022) - [i150]Oriana Peltzer, Amanda Bouman, Sung-Kyun Kim, Ransalu Senanayake, Joshua Ott, Harrison Delecki, Mamoru Sobue, Mykel J. Kochenderfer, Mac Schwager, Joel Burdick, Ali-akbar Agha-mohammadi:
FIG-OP: Exploring Large-Scale Unknown Environments on a Fixed Time Budget. CoRR abs/2203.06316 (2022) - [i149]Christopher Lazarus, Mykel J. Kochenderfer:
A Mixed Integer Programming Approach for Verifying Properties of Binarized Neural Networks. CoRR abs/2203.07078 (2022) - [i148]Harrison Delecki, Masha Itkina, Bernard Lange, Ransalu Senanayake, Mykel J. Kochenderfer:
How Do We Fail? Stress Testing Perception in Autonomous Vehicles. CoRR abs/2203.14155 (2022) - [i147]Dylan M. Asmar, Ransalu Senanayake, Shawn Manuel, Mykel J. Kochenderfer:
Model Predictive Optimized Path Integral Strategies. CoRR abs/2203.16633 (2022) - [i146]Arec L. Jamgochian, Etienne Bührle, Johannes Fischer, Mykel J. Kochenderfer:
SHAIL: Safety-Aware Hierarchical Adversarial Imitation Learning for Autonomous Driving in Urban Environments. CoRR abs/2204.01922 (2022) - [i145]Sydney M. Katz, Luis E. Alvarez, Michael P. Owen, Samuel Wu, Marc Brittain, Anshuman Das, Mykel J. Kochenderfer:
Collision Risk and Operational Impact of Speed Change Advisories as Aircraft Collision Avoidance Maneuvers. CoRR abs/2204.14250 (2022) - [i144]Anthony L. Corso, Sydney M. Katz, Craig Innes, Xin Du, Subramanian Ramamoorthy, Mykel J. Kochenderfer:
Risk-Driven Design of Perception Systems. CoRR abs/2205.10677 (2022) - [i143]Junyoung Park, Federico Berto, Arec L. Jamgochian, Mykel J. Kochenderfer, Jinkyoo Park:
Meta-SysId: A Meta-Learning Approach for Simultaneous Identification and Prediction. CoRR abs/2206.00694 (2022) - [i142]Bertrand Charpentier, Ransalu Senanayake, Mykel J. Kochenderfer, Stephan Günnemann:
Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning. CoRR abs/2206.01558 (2022) - [i141]Liam A. Kruse, Esen Yel, Ransalu Senanayake, Mykel J. Kochenderfer:
Uncertainty-Aware Online Merge Planning with Learned Driver Behavior. CoRR abs/2207.05228 (2022) - [i140]Eric Luxenberg, Stephen P. Boyd, Mykel J. Kochenderfer, Misha van Beek, Wen Cao, Steven Diamond, Alex Ulitsky, Kunal Menda, Vidy Vairavamurthy:
Strategic Asset Allocation with Illiquid Alternatives. CoRR abs/2207.07767 (2022) - 2021
- [j27]Changliu Liu, Tomer Arnon, Christopher Lazarus, Christopher A. Strong, Clark W. Barrett, Mykel J. Kochenderfer:
Algorithms for Verifying Deep Neural Networks. Found. Trends Optim. 4(3-4): 244-404 (2021) - [j26]Shushman Choudhury, Kiril Solovey, Mykel J. Kochenderfer, Marco Pavone:
Efficient Large-Scale Multi-Drone Delivery using Transit Networks. J. Artif. Intell. Res. 70: 757-788 (2021) - [j25]Anthony Corso, Robert J. Moss, Mark Koren, Ritchie Lee, Mykel J. Kochenderfer:
A Survey of Algorithms for Black-Box Safety Validation of Cyber-Physical Systems. J. Artif. Intell. Res. 72: 377-428 (2021) - [j24]Nicholas Moehle, Mykel J. Kochenderfer, Stephen P. Boyd, Andrew Ang:
Tax-Aware Portfolio Construction via Convex Optimization. J. Optim. Theory Appl. 189(2): 364-383 (2021) - [j23]Patrick Slade, Arjun Tambe, Mykel J. Kochenderfer:
Multimodal sensing and intuitive steering assistance improve navigation and mobility for people with impaired vision. Sci. Robotics 6(59) (2021) - [c125]Anthony Corso, Mykel J. Kochenderfer:
Transfer Learning for Efficient Iterative Safety Validation. AAAI 2021: 7125-7132 - [c124]John Mern, Anil Yildiz, Zachary Sunberg, Tapan Mukerji, Mykel J. Kochenderfer:
Bayesian Optimized Monte Carlo Planning. AAAI 2021: 11880-11887 - [c123]John Mern, Anil Yildiz, Lawrence Bush, Tapan Mukerji, Mykel J. Kochenderfer:
Improved POMDP Tree Search Planning with Prioritized Action Branching. AAAI 2021: 11888-11894 - [c122]Shushman Choudhury, Jayesh K. Gupta, Peter Morales, Mykel J. Kochenderfer:
Scalable Anytime Planning for Multi-Agent MDPs. AAMAS 2021: 341-349 - [c121]Sheng Li, Jayesh K. Gupta, Peter Morales, Ross E. Allen, Mykel J. Kochenderfer:
Deep Implicit Coordination Graphs for Multi-agent Reinforcement Learning. AAMAS 2021: 764-772 - [c120]Geoffrey Pettet, Ayan Mukhopadhyay, Mykel J. Kochenderfer, Abhishek Dubey:
Hierarchical planning for resource allocation in emergency response systems. ICCPS 2021: 155-166 - [c119]Liam A. Kruse, Allan L. Reiss, Mykel J. Kochenderfer, Stephanie Balters:
Dyadic Sex Composition and Task Classification Using fNIRS Hyperscanning Data. ICMLA 2021: 582-588 - [c118]Xiaobai Ma, Jiachen Li, Mykel J. Kochenderfer, David Isele, Kikuo Fujimura:
Reinforcement Learning for Autonomous Driving with Latent State Inference and Spatial-Temporal Relationships. ICRA 2021: 6064-6071 - [c117]Maneekwan Toyungyernsub, Masha Itkina, Ransalu Senanayake, Mykel J. Kochenderfer:
Double-Prong ConvLSTM for Spatiotemporal Occupancy Prediction in Dynamic Environments. ICRA 2021: 13931-13937 - [c116]Christopher Lazarus, Mykel J. Kochenderfer:
A Mixed Integer Programming Approach for Verifying Properties of Binarized Neural Networks. AISafety@IJCAI 2021 - [c115]Bernard Lange, Masha Itkina, Mykel J. Kochenderfer:
Attention Augmented ConvLSTM for Environment Prediction. IROS 2021: 1346-1353 - [c114]Ransalu Senanayake, Kyle Beltran Hatch, Jason Zheng, Mykel J. Kochenderfer:
3D Radar Velocity Maps for Uncertain Dynamic Environments. IROS 2021: 4854-4860 - [c113]Mark Koren, Ahmed Nassar, Mykel J. Kochenderfer:
Finding Failures in High-Fidelity Simulation using Adaptive Stress Testing and the Backward Algorithm. IROS 2021: 5944-5949 - [c112]Julia Nitsch, Masha Itkina, Ransalu Senanayake, Juan I. Nieto, Max Schmidt, Roland Siegwart, Mykel J. Kochenderfer, Cesar Cadena:
Out-of-Distribution Detection for Automotive Perception. ITSC 2021: 2938-2943 - [c111]Phil Chen, Masha Itkina, Ransalu Senanayake, Mykel J. Kochenderfer:
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models. NeurIPS 2021: 11565-11576 - [c110]Samriddhi Singla, Ayan Mukhopadhyay, Michael Wilbur, Tina Diao, Vinayak Gajjewar, Ahmed Eldawy, Mykel J. Kochenderfer, Ross D. Shachter, Abhishek Dubey:
WildfireDB: An Open-Source Dataset Connecting Wildfire Occurrence with Relevant Determinants. NeurIPS Datasets and Benchmarks 2021 - [i139]Shushman Choudhury, Jayesh K. Gupta, Peter Morales, Mykel J. Kochenderfer:
Scalable Anytime Planning for Multi-Agent MDPs. CoRR abs/2101.04788 (2021) - [i138]Sheng Li, Yutai Zhou, Ross E. Allen, Mykel J. Kochenderfer:
Learning Emergent Discrete Message Communication for Cooperative Reinforcement Learning. CoRR abs/2102.12550 (2021) - [i137]Sydney M. Katz, Kyle D. Julian, Christopher A. Strong, Mykel J. Kochenderfer:
Generating Probabilistic Safety Guarantees for Neural Network Controllers. CoRR abs/2103.01203 (2021) - [i136]Sydney M. Katz, Amir Maleki, Erdem Biyik, Mykel J. Kochenderfer:
Preference-based Learning of Reward Function Features. CoRR abs/2103.02727 (2021) - [i135]Kunal Menda, Jayesh K. Gupta, Zachary Manchester, Mykel J. Kochenderfer:
Training Structured Mechanical Models by Minimizing Discrete Euler-Lagrange Residual. CoRR abs/2105.01811 (2021) - [i134]Sydney M. Katz, Anthony L. Corso, Christopher A. Strong, Mykel J. Kochenderfer:
Verification of Image-based Neural Network Controllers Using Generative Models. CoRR abs/2105.07091 (2021) - [i133]John Mern, Mykel J. Kochenderfer:
Measurable Monte Carlo Search Error Bounds. CoRR abs/2106.04715 (2021) - [i132]Christopher A. Strong, Sydney M. Katz, Anthony L. Corso, Mykel J. Kochenderfer:
ZoPE: A Fast Optimizer for ReLU Networks with Low-Dimensional Inputs. CoRR abs/2106.05325 (2021) - [i131]John Mern, Kyle Hatch, Ryan Silva, Jeff Brush, Mykel J. Kochenderfer:
Reinforcement Learning for Industrial Control Network Cyber Security Orchestration. CoRR abs/2106.05332 (2021) - [i130]Geoffrey Pettet, Ayan Mukhopadhyay, Mykel J. Kochenderfer, Abhishek Dubey:
Hierarchical Planning for Dynamic Resource Allocation in Smart and Connected Communities. CoRR abs/2107.01292 (2021) - [i129]Ransalu Senanayake, Kyle Beltran Hatch, Jason Zheng, Mykel J. Kochenderfer:
3D Radar Velocity Maps for Uncertain Dynamic Environments. CoRR abs/2107.11039 (2021) - [i128]Mark Koren, Ahmed Nassar, Mykel J. Kochenderfer:
Finding Failures in High-Fidelity Simulation using Adaptive Stress Testing and the Backward Algorithm. CoRR abs/2107.12940 (2021) - [i127]Chelsea Sidrane, Amir Maleki, Ahmed Irfan, Mykel J. Kochenderfer:
OVERT: An Algorithm for Safety Verification of Neural Network Control Policies for Nonlinear Systems. CoRR abs/2108.01220 (2021) - [i126]Raunak P. Bhattacharyya, Soyeon Jung, Liam Kruse, Ransalu Senanayake, Mykel J. Kochenderfer:
A Hybrid Rule-Based and Data-Driven Approach to Driver Modeling through Particle Filtering. CoRR abs/2108.12820 (2021) - [i125]Masha Itkina, Ye-Ji Mun, Katherine Driggs Campbell, Mykel J. Kochenderfer:
Multi-Agent Variational Occlusion Inference Using People as Sensors. CoRR abs/2109.02173 (2021) - [i124]John Mern, Sidhart Krishnan, Anil Yildiz, Kyle Hatch, Mykel J. Kochenderfer:
Interpretable Local Tree Surrogate Policies. CoRR abs/2109.08180 (2021) - [i123]Shushman Choudhury, Kiril Solovey, Mykel J. Kochenderfer, Marco Pavone:
Coordinated Multi-Agent Pathfinding for Drones and Trucks over Road Networks. CoRR abs/2110.08802 (2021) - [i122]Phil Chen, Masha Itkina, Ransalu Senanayake, Mykel J. Kochenderfer:
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models. CoRR abs/2110.14182 (2021) - [i121]John Mern, Kyle Hatch, Ryan Silva, Cameron Hickert, Tamim Sookoor, Mykel J. Kochenderfer:
Autonomous Attack Mitigation for Industrial Control Systems. CoRR abs/2111.02445 (2021) - [i120]Liam A. Kruse, Allan L. Reiss, Mykel J. Kochenderfer, Stephanie Balters:
Dyadic Sex Composition and Task Classification Using fNIRS Hyperscanning Data. CoRR abs/2112.03911 (2021) - 2020
- [j22]Bohan Wu, Jayesh K. Gupta, Mykel J. Kochenderfer:
Model primitives for hierarchical lifelong reinforcement learning. Auton. Agents Multi Agent Syst. 34(1): 28 (2020) - [j21]Patrick Slade, Zachary N. Sunberg, Mykel J. Kochenderfer:
Estimation and control using sampling-based Bayesian reinforcement learning. IET Cyper-Phys. Syst.: Theory & Appl. 5(1): 127-135 (2020) - [j20]Ritchie Lee, Ole J. Mengshoel, Anshu Saksena, Ryan W. Gardner, Daniel Genin, Joshua Silbermann, Michael P. Owen, Mykel J. Kochenderfer:
Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning. J. Artif. Intell. Res. 69: 1165-1201 (2020) - [j19]Carl-Johan Hoel, Katherine Rose Driggs-Campbell, Krister Wolff, Leo Laine, Mykel J. Kochenderfer:
Combining Planning and Deep Reinforcement Learning in Tactical Decision Making for Autonomous Driving. IEEE Trans. Intell. Veh. 5(2): 294-305 (2020) - [c109]Maxime Bouton, Jana Tumova, Mykel J. Kochenderfer:
Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes. AAAI 2020: 10061-10068 - [c108]Shushman Choudhury, Nate Gruver, Mykel J. Kochenderfer:
Adaptive Informative Path Planning with Multimodal Sensing. ICAPS 2020: 57-65 - [c107]Raunak P. Bhattacharyya, Ransalu Senanayake, Kyle Brown, Mykel J. Kochenderfer:
Online Parameter Estimation for Human Driver Behavior Prediction. ACC 2020: 301-306 - [c106]John Mern, Dorsa Sadigh, Mykel J. Kochenderfer:
Exchangeable Input Representations for Reinforcement Learning. ACC 2020: 3971-3976 - [c105]Geoffrey Pettet, Ayan Mukhopadhyay, Mykel J. Kochenderfer, Yevgeniy Vorobeychik, Abhishek Dubey:
On Algorithmic Decision Procedures in Emergency Response Systems in Smart and Connected Communities. AAMAS 2020: 1046-1054 - [c104]Nate Gruver, Jiaming Song, Mykel J. Kochenderfer, Stefano Ermon:
Multi-agent Adversarial Inverse Reinforcement Learning with Latent Variables. AAMAS 2020: 1855-1857 - [c103]Xiaobai Ma, Jayesh K. Gupta, Mykel J. Kochenderfer:
Normalizing Flow Model for Policy Representation in Continuous Action Multi-agent Systems. AAMAS 2020: 1916-1918 - [c102]Xiaobai Ma, Jayesh K. Gupta, Mykel J. Kochenderfer:
Normalizing Flow Policies for Multi-agent Systems. GameSec 2020: 277-296 - [c101]Kunal Menda, Jean de Becdelièvre, Jayesh K. Gupta, Ilan Kroo, Mykel J. Kochenderfer, Zachary Manchester:
Scalable Identification of Partially Observed Systems with Certainty-Equivalent EM. ICML 2020: 6830-6840 - [c100]Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill:
Learning Near Optimal Policies with Low Inherent Bellman Error. ICML 2020: 10978-10989 - [c99]Jean-Raymond Betterton, Daniel Ratner, Samuel Webb, Mykel J. Kochenderfer:
Reinforcement Learning for Adaptive Illumination with X-rays. ICRA 2020: 328-334 - [c98]Kyle Brown, Oriana Peltzer, Martin A. Sehr, Mac Schwager, Mykel J. Kochenderfer:
Optimal Sequential Task Assignment and Path Finding for Multi-Agent Robotic Assembly Planning. ICRA 2020: 441-447 - [c97]Shushman Choudhury, Kiril Solovey, Mykel J. Kochenderfer, Marco Pavone:
Efficient Large-Scale Multi-Drone Delivery Using Transit Networks. ICRA 2020: 4543-4550 - [c96]Maxime Bouton, Alireza Nakhaei, David Isele, Kikuo Fujimura, Mykel J. Kochenderfer:
Reinforcement Learning with Iterative Reasoning for Merging in Dense Traffic. ITSC 2020: 1-6 - [c95]Anthony Corso, Mykel J. Kochenderfer:
Interpretable Safety Validation for Autonomous Vehicles. ITSC 2020: 1-6 - [c94]Anthony Corso, Ritchie Lee, Mykel J. Kochenderfer:
Scalable Autonomous Vehicle Safety Validation through Dynamic Programming and Scene Decomposition. ITSC 2020: 1-6 - [c93]Kyle D. Julian, Ritchie Lee, Mykel J. Kochenderfer:
Validation of Image-Based Neural Network Controllers through Adaptive Stress Testing. ITSC 2020: 1-7 - [c92]Mark Koren, Mykel J. Kochenderfer:
Adaptive Stress Testing without Domain Heuristics using Go-Explore. ITSC 2020: 1-6 - [c91]Ransalu Senanayake, Maneekwan Toyungyernsub, Mingyu Wang, Mykel J. Kochenderfer, Mac Schwager:
Directional Primitives for Uncertainty-Aware Motion Estimation in Urban Environments. ITSC 2020: 1-6 - [c90]Jayesh K. Gupta, Kunal Menda, Zachary Manchester, Mykel J. Kochenderfer:
Structured Mechanical Models for Robot Learning and Control. L4DC 2020: 328-337 - [c89]Masha Itkina, Boris Ivanovic, Ransalu Senanayake, Mykel J. Kochenderfer, Marco Pavone:
Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational Autoencoders. NeurIPS 2020 - [c88]Jiaxuan You, Xiaobai Ma, Daisy Yi Ding, Mykel J. Kochenderfer, Jure Leskovec:
Handling Missing Data with Graph Representation Learning. NeurIPS 2020 - [c87]Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill:
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration. NeurIPS 2020 - [c86]Erdem Biyik, Nicolas Huynh, Mykel J. Kochenderfer, Dorsa Sadigh:
Active Preference-Based Gaussian Process Regression for Reward Learning. Robotics: Science and Systems 2020 - [c85]Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer, Dorsa Sadigh, Jeannette Bohg:
Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints. Robotics: Science and Systems 2020 - [c84]Ayan Mukhopadhyay, Kai Wang, Andrew Perrault, Mykel J. Kochenderfer, Milind Tambe, Yevgeniy Vorobeychik:
Robust Spatial-Temporal Incident Prediction. UAI 2020: 360-369 - [i119]Maxime Bouton, Jana Tumova, Mykel J. Kochenderfer:
Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes. CoRR abs/2001.03809 (2020) - [i118]Geoffrey Pettet, Ayan Mukhopadhyay, Mykel J. Kochenderfer, Yevgeniy Vorobeychik, Abhishek Dubey:
On Algorithmic Decision Procedures in Emergency Response Systems in Smart and Connected Communities. CoRR abs/2001.07362 (2020) - [i117]Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill:
Learning Near Optimal Policies with Low Inherent Bellman Error. CoRR abs/2003.00153 (2020) - [i116]Kyle D. Julian, Ritchie Lee, Mykel J. Kochenderfer:
Validation of Image-Based Neural Network Controllers through Adaptive Stress Testing. CoRR abs/2003.02381 (2020) - [i115]John Mern, Dorsa Sadigh, Mykel J. Kochenderfer:
Exchangeable Input Representations for Reinforcement Learning. CoRR abs/2003.09022 (2020) - [i114]Shushman Choudhury, Nate Gruver, Mykel J. Kochenderfer:
Adaptive Informative Path Planning with Multimodal Sensing. CoRR abs/2003.09746 (2020) - [i113]Mark Koren, Mykel J. Kochenderfer:
Adaptive Stress Testing without Domain Heuristics using Go-Explore. CoRR abs/2004.04292 (2020) - [i112]Mark Koren, Anthony Corso, Mykel J. Kochenderfer:
The Adaptive Stress Testing Formulation. CoRR abs/2004.04293 (2020) - [i111]Anthony Corso, Ritchie Lee, Mykel J. Kochenderfer:
Scalable Autonomous Vehicle Safety Validation through Dynamic Programming and Scene Decomposition. CoRR abs/2004.06801 (2020) - [i110]Anthony Corso, Mykel J. Kochenderfer:
Interpretable Safety Validation for Autonomous Vehicles. CoRR abs/2004.06805 (2020) - [i109]Oriana Peltzer, Kyle Brown, Mac Schwager, Mykel J. Kochenderfer, Martin A. Sehr:
STT-CBS: A Conflict-Based Search Algorithm for Multi-Agent Path Finding with Stochastic Travel Times. CoRR abs/2004.08025 (2020) - [i108]Jayesh K. Gupta, Kunal Menda, Zachary Manchester, Mykel J. Kochenderfer:
Structured Mechanical Models for Robot Learning and Control. CoRR abs/2004.10301 (2020) - [i107]Erdem Biyik, Nicolas Huynh, Mykel J. Kochenderfer, Dorsa Sadigh:
Active Preference-Based Gaussian Process Regression for Reward Learning. CoRR abs/2005.02575 (2020) - [i106]Raunak P. Bhattacharyya, Ransalu Senanayake, Kyle Brown, Mykel J. Kochenderfer:
Online Parameter Estimation for Human Driver Behavior Prediction. CoRR abs/2005.02597 (2020) - [i105]Anthony Corso, Robert J. Moss, Mark Koren, Ritchie Lee, Mykel J. Kochenderfer:
A Survey of Algorithms for Black-Box Safety Validation. CoRR abs/2005.02979 (2020) - [i104]Maxime Bouton, Alireza Nakhaei, David Isele, Kikuo Fujimura, Mykel J. Kochenderfer:
Reinforcement Learning with Iterative Reasoning for Merging in Dense Traffic. CoRR abs/2005.11895 (2020) - [i103]Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer, Dorsa Sadigh, Jeannette Bohg:
Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints. CoRR abs/2005.13109 (2020) - [i102]Zachary Sunberg, Mykel J. Kochenderfer:
Improving Automated Driving through Planning with Human Internal States. CoRR abs/2005.14549 (2020) - [i101]