Source: http://mykel.kochenderfer.com/publications/
Timestamp: 2019-04-22 14:49:17+00:00

Document:
K. D. Julian, M. J. Kochenderfer, and M. P. Owen, “Deep neural network compression for aircraft collision avoidance systems,” Journal of Guidance, Control, and Dynamics, vol. 42, iss. 3, p. 598–608, 2019.
M. J. Kochenderfer and T. A. Wheeler, Algorithms for Optimization, MIT Press, 2019.
R. Lee, O. J. Mengshoel, A. Agogino, D. Giannakoupoulou, and M. J. Kochenderfer, “Adaptive stress testing of trajectory planning systems,” in AIAA Science and Technology Forum (SciTech), 2019.
K. Menda, Y. Chen, J. Grana, J. W. Bono, B. D. Tracey, M. J. Kochenderfer, and D. H. Wolpert, “Deep reinforcement learning for event-driven multi-agent decision processes,” IEEE Transactions on Intelligent Transportation Systems, vol. 20, iss. 4, p. 1259–1268, 2019.
J. Mern, K. D. Julian, R. E. Tompa, and M. J. Kochenderfer, “Visual depth mapping from monocular images using recurrent convolutional neural networks,” in AIAA Science and Technology Forum (SciTech), 2019.
M. Kelly, C. R. Sidrane, K. R. Driggs-Campbell, and M. J. Kochenderfer, “HG-DAgger: interactive imitation learning with human experts,” in IEEE International Conference on Robotics and Automation (ICRA), 2019.
R. Bhattacharyya, D. J. Phillips, C. Liu, J. K. Gupta, K. R. Driggs-Campbell, and M. J. Kochenderfer, “Simulating emergent properties of human driving behavior using multi-agent reward augmented imitation learning,” in IEEE International Conference on Robotics and Automation (ICRA), 2019.
L. Dressel and M. J. Kochenderfer, “Hunting drones with other drones: tracking a moving radio target,” in IEEE International Conference on Robotics and Automation (ICRA), 2019.
B. Wu, J. K. Gupta, and M. J. Kochenderfer, “Model primitive hierarchical lifelong reinforcement learning,” in International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2019.
J. Mern, D. Sadigh, and M. J. Kochenderfer, “Object exchangability in reinforcement learning,” in International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2019.
R. Lee and M. J. Kochenderfer, “Adaptive stress testing of safety-critical systems,” in Safe, Autonomous and Intelligent Vehicles, H. Yu, X. Li, R. Murray, S. Ramesh, and C. J. Tomlin, Eds., Springer, 2019.
K. D. Julian and M. J. Kochenderfer, “Distributed wildfire surveillance with autonomous aircraft using deep reinforcement learning,” Journal of Guidance, Control, and Dynamics, 2019.
J. Morton, F. D. Witherden, and M. J. Kochenderfer, “Deep variational Koopman models: Inferring Koopman observations for uncertainty-aware dynamics modeling and control,” ArXiv, iss. 1902.09742, 2019.
J. K. Gupta, K. Menda, Z. Manchester, and M. J. Kochenderfer, “A general framework for structured learning of mechanical systems,” ArXiv, iss. 1902.08705, 2019.
D. J. Phillips, J. C. Aragon, A. Roychowdhury, R. Madigan, S. Chintakindi, and M. J. Kochenderfer, “Real-time prediction of automotive collision risk from monocular video,” ArXiv, iss. 1902.01293, 2019.
K. D. Julian, S. Sharma, J. Jeannin, and M. J. Kochenderfer, “Verifying aircraft collision avoidance neural networks through linear approximations of safe regions,” in AIAA Spring Symposium, 2019.
K. D. Julian and M. J. Kochenderfer, “A reachability method for verifying dynamical systems with deep neural network controllers,” ArXiv, iss. 1903.00520, 2019.
C. Liu, T. Arnon, C. Lazarus, C. Barrett, and M. J. Kochenderfer, “Algorithms for verifying deep neural networks,” ArXiv, iss. 1903.06758, 2019.
R. E. Tompa and M. J. Kochenderfer, “Efficient aircraft rerouting during commerical space launches,” New Space, vol. 7, iss. 1, p. 12–18, 2019.
K. D. Julian and M. J. Kochenderfer, “Guaranteeing safety for neural network-based aircraft collision avoidance systems,” in Digital Avionics Systems Conference (DASC), 2019.
S. Jung and M. J. Kochenderfer, “Learning terminal airspace traffic models from flight tracks and procedures,” in Digital Avionics Systems Conference (DASC), 2019.
R. E. Tompa and M. J. Kochenderfer, “Optimal aircraft metering during space launches,” in Digital Avionics Systems Conference (DASC), 2019.
S. M. Katz, A. LeBihan, and M. J. Kochenderfer, “Learning an urban air mobility encounter model from expert preferences,” in Digital Avionics Systems Conference (DASC), 2019.
T. A. Wheeler and M. J. Kochenderfer, “Critical situation clusters for accelerated automotive safety validation,” in IEEE Intelligent Vehicles Symposium (IV), 2019.
S. Choudhury and M. J. Kochenderfer, “Dynamic real-time multimodal routing with hierarchical hybrid planning,” in IEEE Intelligent Vehicles Symposium (IV), 2019.
M. Schratter, M. Bouton, M. J. Kochenderfer, and D. Watzenig, “Pedestrian collision avoidance system for scenarios with occlusions,” in IEEE Intelligent Vehicles Symposium (IV), 2019.
M. Bouton, A. Nakhaei, K. Fujimura, and M. J. Kochenderfer, “Safe reinforcement learning with scene decomposition for navigating complex urban environments,” in IEEE Intelligent Vehicles Symposium (IV), 2019.
S. Li, M. Egorov, and M. J. Kochenderfer, “Optimizing collision avoidance in dense airspace using deep reinforcement learning,” in Air Traffic Management Research and Development Seminar, 2019.
M. Bouton, K. D. Julian, A. Nakhaei, K. Fujimura, and M. J. Kochenderfer, “Decomposition methods with deep corrections for reinforcement learning,” Autonomous Agents and Multi-Agent Systems, 2019.
O. Afolabi, K. R. Driggs-Campbell, R. Dong, M. J. Kochenderfer, and S. Sastry, “People as sensors: Imputing maps from human actions,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018.
E. Balaban, S. B. Johnson, and M. J. Kochenderfer, “Rethinking system health management,” in AAAI Fall Symposium on Integrating Planning, Diagnosis, and Causal Reasoning, 2018.
S. T. Barratt, M. J. Kochenderfer, and S. P. Boyd, “Learning probabilistic trajectory models of aircraft in terminal airspace from position data,” IEEE Transactions on Intelligent Transportation Systems, 2018.
R. Bhattacharyya, D. J. Phillips, B. Wulfe, J. Morton, A. Kuefler, and M. J. Kochenderfer, “Multi-agent imitation learning for driving simulation,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018.
M. Bouton, K. D. Julian, A. Nakhaei, K. Fujimura, and M. J. Kochenderfer, “Utility decomposition with deep corrections for scalable planning under uncertainty,” in International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2018.
M. Bouton, J. Karlsson, A. Nakhaei, K. Fujimura, M. J. Kochenderfer, and J. Tumova, “Reinforcement learning with probabilistic guarantees for autonomous driving,” in Workshop on Safety Risk and Uncertainty in Reinforcement Learning, Conference on Uncertainty in Artificial Intelligence (UAI), 2018.
M. Bouton, A. Nakhaei, K. Fujimura, and M. J. Kochenderfer, “Scalable decision making with sensor occlusions for autonomous driving,” in IEEE International Conference on Robotics and Automation (ICRA), 2018.
K. T. Carlberg, A. Jameson, M. J. Kochenderfer, J. Morton, L. Peng, and F. D. Witherden, “Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning,” ArXiv, iss. 1812.01177, 2018.
Y. Chen, M. J. Kochenderfer, and M. T. J. Spaan, “Improving offline value-function approximations for POMDPs by reducing discount factors,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018.
S. Choudhury, N. Gruver, and M. J. Kochenderfer, “Online stochastic planning for multimodal sensing and navigation under uncertainty,” in Workshop on Multi-Modal Perception and Control, Robotics: Science and Systems, 2018.
L. Dressel and M. J. Kochenderfer, “Efficient and low-cost localization of radio signals with a multirotor UAV,” in AIAA Guidance, Navigation, and Control Conference (GNC), 2018.
L. Dressel and M. J. Kochenderfer, “On the optimality of ergodic trajectories for information gathering tasks,” in American Control Conference (ACC), 2018.
L. Dressel and M. J. Kochenderfer, “Using neural networks to generate information maps for mobile sensors,” in IEEE Conference on Decision and Control (CDC), 2018.
L. Dressel and M. J. Kochenderfer, “Pseudo-bearing measurements for improved localization of radio sources with multirotor UAVs,” in IEEE International Conference on Robotics and Automation (ICRA), 2018.
L. Dressel and M. J. Kochenderfer, “Tutorial on the generation of ergodic trajectories with projection-based gradient descent,” IET Cyber-Physical Systems: Theory and Applications, 2018.
K. D. Julian and M. J. Kochenderfer, “Image-based guidance of autonomous aircraft for wildfire surveillance and prediction,” ArXiv, iss. 1810.02455, 2018.
M. Kelly, C. R. Sidrane, K. R. Driggs-Campbell, and M. J. Kochenderfer, “Safe interactive imitation learning from humans,” in Imitation Learning and its Challenges in Robotics Workshop, Advances in Neural Information Processing Systems (NIPS), 2018.
M. Koren, S. Alsaif, R. Lee, and M. J. Kochenderfer, “Adaptive stress testing for autonomous vehicles,” in IEEE Intelligent Vehicles Symposium (IV), 2018.
A. Kuefler and M. J. Kochenderfer, “Burn-in demonstrations for multi-modal imitation learning,” in International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2018.
L. Kuper, G. Katz, J. Gottschlich, K. D. Julian, C. Barrett, and M. J. Kochenderfer, “Toward scalable verification for safety-critical deep networks,” in SysML, 2018.
R. Lee, M. J. Kochenderfer, O. J. Mengshoel, and J. Silbermann, “Interpretable categorization of heterogeneous time series data,” in SIAM International Conference on Data Mining, 2018.
R. Lee, O. J. Mengshoel, A. Saksena, R. Gardner, D. Genin, J. S. Brush, and M. J. Kochenderfer, “Differential adaptive stress testing of airborne collision avoidance systems,” in AIAA Modeling and Simulation Conference, 2018.
R. Lee, O. J. Mengshoel, A. Saksena, R. Gardner, D. Genin, J. Silbermann, M. P. Owen, and M. J. Kochenderfer, “Adaptive stress testing: finding failure events with reinforcement learning,” ArXiv, iss. 1811.02188, 2018.
C. Liu and M. J. Kochenderfer, “Analytically modeling unmanaged intersections with microscopic vehicle interactions,” in IEEE International Conference on Intelligent Transportation Systems (ITSC), 2018.
C. Liu and M. J. Kochenderfer, “Analyzing Traffic Delay at Unmanaged Intersections,” ArXiv, iss. 1806.02660, 2018.
X. Ma, K. R. Driggs-Campbell, and M. J. Kochenderfer, “Improved robustness, safety, and efficiency with adversarial reinforcement learning,” in IEEE Intelligent Vehicles Symposium (IV), 2018.
K. Menda, K. R. Driggs-Campbell, and M. J. Kochenderfer, “EnsembleDAgger: a Bayesian approach to safe imitation learning,” ArXiv, 2018.
J. Morton, T. A. Wheeler, and M. J. Kochenderfer, “Closed-loop policies for operational tests of safety-critical systems,” IEEE Transactions on Intelligent Transportation Systems, vol. 3, iss. 3, pp. 317-328, 2018.
J. Morton, F. D. Witherden, A. Jameson, and M. J. Kochenderfer, “Deep dynamical modeling and control of unsteady fluid flows,” in Advances in Neural Information Processing Systems (NIPS), 2018.
P. Rosello and M. J. Kochenderfer, “Multi-agent reinforcement learning for multi-object tracking,” in International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2018.
R. Shu, H. H. Bui, S. Zhao, M. J. Kochenderfer, and S. Ermon, “Theoretical Foundations and Applications of Deep Generative Models,” in Workshop on Theoretical Foundations and Applications of Deep Generative Models, International Conference on Machine Learning (ICML), 2018.
R. Shu, H. H. Bui, S. Zhao, M. J. Kochenderfer, and S. Ermon, “Amortized inference regularization,” in Advances in Neural Information Processing Systems (NIPS), 2018.
R. Shu, S. Zhao, and M. J. Kochenderfer, “Rethinking style and content disentanglement in variational autoencoders,” in International Conference on Learning Representations (Workshop Track), 2018.
C. R. Sidrane and M. J. Kochenderfer, “Closed-loop planning for disaster evacuation with stochastic arrivals,” in IEEE International Conference on Intelligent Transportation Systems (ITSC), 2018.
P. Slade, Z. N. Sunberg, and M. J. Kochenderfer, “Estimation and control using sampling-based Bayesian reinforcement learning,” ArXiv, iss. 1808.00888, 2018.
P. Slade, R. Troutman, M. J. Kochenderfer, S. H. Collins, and S. L. Delp, “Rapid energy expenditure estimation for assisted and inclined loaded walking,” bioRxiv, 2018.
E. Sonu, Z. N. Sunberg, and M. J. Kochenderfer, “Exploiting hierarchy for scalable decision making in autonomous driving,” in IEEE Intelligent Vehicles Symposium (IV), 2018.
S. Thornton, F. E. Lewis, V. Zhang, M. J. Kochenderfer, and C. J. Gerdes, “Value sensitive design for autonomous vehicle motion planning,” in IEEE Intelligent Vehicles Symposium (IV), 2018.
R. E. Tompa and M. J. Kochenderfer, “Optimal aircraft rerouting during space launches using adaptive spatial discretization,” in Digital Avionics Systems Conference (DASC), 2018.
R. E. Tompa, B. Wulfe, M. J. Kochenderfer, and M. P. Owen, “Horizontal maneuver coordination for aircraft collision-avoidance systems,” Journal of Aerospace Information Systems, vol. 15, iss. 2, pp. 92-106, 2018.
J. M. Walker, A. M. Okamura, and M. J. Kochenderfer, “Gaussian process dynamic programming for optimizing ungrounded haptic guidance,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018.
B. Wulfe, M. J. Kochenderfer, S. Chintakindi, S. C. Choi, R. Hartong-Redden, and A. Kodali, “Real-time prediction of intermediate-horizon automotive collision risk,” in International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2018.
A. Zanette, J. Zhang, and M. J. Kochenderfer, “Robust super-level set estimation using Gaussian processes,” in European Conference on Machine Learning (ECML), 2018.
Z. Zhang and M. J. Kochenderfer, “Decision-theoretic planning in partially observable environments,” in Interactions in Multiagent Systems, J. Hao and H. Leung, Eds., World Scientific, 2018, pp. 65-90.
D. Bertsimas, D. J. Griffith, V. Gupta, M. J. Kochenderfer, and V. V. Misic, “A comparison of Monte Carlo tree search and rolling horizon optimization for large-scale dynamic resource allocation problems,” European Journal of Operational Research, vol. 263, iss. 2, pp. 664-678, 2017.
Y. Chen, T. A. Wheeler, and M. J. Kochenderfer, “Learning discrete Bayesian networks from continuous data,” Journal of Artificial Intelligence Research, vol. 59, pp. 103-132, 2017.
L. Dressel and M. J. Kochenderfer, “Efficient decision-theoretic target localization,” in International Conference on Automated Planning and Scheduling (ICAPS), 2017.
D. J. Griffith, M. J. Kochenderfer, R. J. Moss, V. V. Misic, V. Gupta, and D. Bertsimas, “Automated dynamic resource allocation for wildfire suppression,” Lincoln Laboratory Journal, vol. 22, iss. 2, pp. 38-59, 2017.
K. D. Julian and M. J. Kochenderfer, “Neural network guidance for UAVs,” in AIAA Guidance, Navigation, and Control Conference (GNC), 2017.
Y. Kim, Y. Gur, and M. J. Kochenderfer, “Heuristics for planning with rare catastrophic events,” in Winter Simulation Conference, 2017.
A. Kuefler and M. J. Kochenderfer, “Burn-in demonstrations for multi-modal imitation learning,” in Conference on Robotic Learning, 2017.
A. Kuefler, M. J. Kochenderfer, and J. L. McClelland, “Geometric concept acquisition in a dueling deep Q-network,” in Annual Meeting of the Cognitive Science Society, 2017.
Z. Mahboubi and M. J. Kochenderfer, “Learning traffic patterns at small airports from flight tracks,” IEEE Transactions on Intelligent Transportation Systems, vol. 18, iss. 4, pp. 917-926, 2017.
J. Mern, J. K. Gupta, and M. J. Kochenderfer, “Layer-wise synapse optimization for implementing neural networks on general neuromorphic architectures,” in IEEE Symposium Series on Computational Intelligence, 2017.
J. Morton and M. J. Kochenderfer, “Simultaneous policy learning and latent state inference for imitating driver behavior,” in IEEE International Conference on Intelligent Transportation Systems (ITSC), 2017.
H. Y. Ong and M. J. Kochenderfer, “Markov decision process-based distributed conflict resolution for drone air traffic management,” Journal of Guidance, Control, and Dynamics, vol. 40, iss. 1, pp. 69-80, 2017.
D. J. Phillips, T. A. Wheeler, and M. J. Kochenderfer, “Generalizable intention prediction of human drivers at intersections,” in IEEE Intelligent Vehicles Symposium (IV), 2017.
P. Slade, P. Culbertson, Z. N. Sunberg, and M. J. Kochenderfer, “Simultaneous active parameter estimation and control using sampling-based Bayesian reinforcement learning,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017.
Z. N. Sunberg, C. Ho, and M. J. Kochenderfer, “The value of inferring the internal state of traffic participants for autonomous freeway driving,” in American Control Conference (ACC), 2017.
T. A. Wheeler, M. F. Holder, H. Winner, and M. J. Kochenderfer, “Deep stochastic radar models,” in IEEE Intelligent Vehicles Symposium (IV), 2017.
Z. Zhang, Z. Pan, and M. J. Kochenderfer, “Weighted double Q-learning,” in International Joint Conference on Artificial Intelligence (IJCAI), 2017.
J. Cox and M. J. Kochenderfer, “Probabilistic airport acceptance rate prediction,” in AIAA Modeling and Simulation Conference, San Diego, Calif., 2016.
J. Cox and M. J. Kochenderfer, “Ground delay program planning using Markov decision processes,” Journal of Aerospace Information Systems, vol. 13, iss. 3, pp. 134-142, 2016.
M. Egorov, M. J. Kochenderfer, and J. J. Uudmae, “Target surveillance in adversarial environments using POMDPs,” in AAAI Conference on Artificial Intelligence (AAAI), 2016.
K. D. Julian, J. Lopez, J. S. Brush, M. P. Owen, and M. J. Kochenderfer, “Policy compression for aircraft collision avoidance systems,” in Digital Avionics Systems Conference (DASC), 2016.
Y. Kim and M. J. Kochenderfer, “Improving aircraft collision risk estimation using the cross-entropy method,” Journal of Air Transportation, vol. 24, iss. 2, pp. 55-61, 2016.
V. Mehta, P. Rowe, G. Lewis, A. Magalhaes, and M. J. Kochenderfer, “Decision-theoretic approach to designing cyber resilient systems,” in IEEE International Symposium on Network Computing and Applications, 2016.
E. Mueller and M. J. Kochenderfer, “Simulation comparison of collision avoidance algorithms for small multi-rotor aircraft,” in AIAA Modeling and Simulation Conference, 2016.
E. Mueller and M. J. Kochenderfer, “Multi-rotor aircraft collision avoidance using partially observable Markov decision processes,” in AIAA Modeling and Simulation Conference, 2016.
A. Nuttall, M. J. Kochenderfer, and S. Close, “Detection of hypervelocity impact radio frequency pulses through prior constrained source separation,” Radio Science, vol. 51, iss. 10, pp. 1660-1675, 2016.
M. P. Owen and M. J. Kochenderfer, “Dynamic logic selection for unmanned aircraft separation,” in Digital Avionics Systems Conference (DASC), Sacramento, Calif., 2016.
P. Robbel, F. A. Oliehoek, and M. J. Kochenderfer, “Exploiting anonymity in approximate linear programming: scaling to large multiagent MDPs,” in AAAI Conference on Artificial Intelligence (AAAI), 2016.
R. Shu, J. Brofos, F. Zhang, H. H. Bui, M. Ghavamzadeh, and M. J. Kochenderfer, “Stochastic video prediction with conditional density estimation,” in Workshop on Action and Anticipation for Visual Learning, 2016.
Z. N. Sunberg, M. J. Kochenderfer, and M. Pavone, “Optimized and trusted collision avoidance for unmanned aerial vehicles using approximate dynamic programming,” in IEEE International Conference on Robotics and Automation (ICRA), 2016.
Y. Tkachenko, M. J. Kochenderfer, and K. Kluza, “Customer simulation for direct marketing experiments,” in IEEE International Conference on Data Science and Advanced Analytics (DSAA), Montreal, Canada, 2016.
R. E. Tompa, B. Wulfe, M. P. Owen, and M. J. Kochenderfer, “Collision avoidance for unmanned aircraft using coordination tables,” in Digital Avionics Systems Conference (DASC), 2016.
T. A. Wheeler and M. J. Kochenderfer, “Factor graph scene distributions for automotive safety analysis,” in IEEE International Conference on Intelligent Transportation Systems (ITSC), Rio de Janeiro, Brazil, 2016.
T. A. Wheeler, P. Robbel, and M. J. Kochenderfer, “Analysis of microscopic behavior models for probabilistic modeling of driver behavior,” in IEEE International Conference on Intelligent Transportation Systems (ITSC), Rio de Janeiro, Brazil, 2016.
J. Cox and M. J. Kochenderfer, “Optimization approaches to the single airport ground hold problem,” in AIAA Guidance, Navigation, and Control Conference (GNC), Kissimmee, FL, 2015.
J. Cox and M. J. Kochenderfer, “Optimization approaches to the single airport ground holding problem,” Journal of Guidance, Control, and Dynamics, vol. 38, iss. 12, pp. 2399-2406, 2015.
L. Dressel and M. J. Kochenderfer, “Signal source localization using partially observable Markov decision processes,” in AIAA Infotech@Aerospace Conference, Kissimmee, FL, 2015.
C. Ho, M. J. Kochenderfer, V. Mehta, and R. S. Caceres, “Control of epidemics on graphs,” in IEEE Conference on Decision and Control (CDC), Osaka, Japan, 2015.
Y. Kim and M. J. Kochenderfer, “Improving aircraft collision risk estimation using the cross-entropy method,” in AIAA Modeling and Simulation Conference, Kissimmee, FL, 2015.
Y. Kim, M. J. Kochenderfer, J. Grana, J. Bono, and D. H. Wolpert, “Optimal lost-link policies for unmanned aircraft,” in Digital Avionics Systems Conference (DASC), 2015.
M. J. Kochenderfer, Decision Making Under Uncertainty: Theory and Application, MIT Press, 2015.
J. R. Lepird, M. P. Owen, and M. J. Kochenderfer, “Bayesian preference elicitation for multiobjective engineering design optimization,” Journal of Aerospace Information Systems, vol. 12, iss. 10, pp. 634-645, 2015.
Z. Mahboubi and M. J. Kochenderfer, “Autonomous air traffic control for non-towered airports,” in Air Traffic Management Research and Development Seminar, 2015.
Z. Mahboubi and M. J. Kochenderfer, “Continuous time autonomous air traffic control for non-towered airports,” in IEEE Conference on Decision and Control (CDC), Osaka, Japan, 2015.
H. Y. Ong and M. J. Kochenderfer, “Short-term conflict resolution for unmanned aircraft traffic management,” in Digital Avionics Systems Conference (DASC), 2015.
K. A. Smith, A. E. Vela, M. J. Kochenderfer, and W. A. Olson, “Optimizing a collision-avoidance system for closely spaced parallel operations,” Journal of Aerospace Information Systems, vol. 12, iss. 10, pp. 618-633, 2015.
R. E. Tompa, M. J. Kochenderfer, R. Cole, and J. K. Kuchar, “Optimal aircraft rerouting during commercial space launches,” in Digital Avionics Systems Conference (DASC), 2015.
T. A. Wheeler, P. Robbel, and M. J. Kochenderfer, “Initial scene configurations for highway traffic propagation,” in IEEE International Conference on Intelligent Transportation Systems (ITSC), Las Palmas de Gran Canaria, Spain, 2015.
D. Bertsimas, D. J. Griffith, V. Gupta, M. J. Kochenderfer, V. V. Misic, and R. J. Moss, “A comparison of Monte Carlo tree search and mathematical optimization for large scale dynamic resource allocation,” ArXiv, 2014.
A. Panken and M. J. Kochenderfer, “Error model estimation for airborne beacon-based surveillance,” IET Radar, Sonar and Navigation, vol. 8, iss. 6, pp. 667-675, 2014.
C. Amato, G. Chowdhary, A. Geramifard, N. K. Ure, and M. J. Kochenderfer, “Decentralized control of partially observable Markov decision processes,” in IEEE Conference on Decision and Control (CDC), 2013.
D. M. Asmar and M. J. Kochenderfer, “Optimized airborne collision avoidance in mixed equipage environments,” Massachusetts Institute of Technology, Lincoln Laboratory, Project Report ATC-408, 2013.
D. M. Asmar, M. J. Kochenderfer, and J. P. Chryssanthacopoulos, “Vertical state estimation for aircraft collision avoidance with quantized measurements,” Journal of Guidance, Control, and Dynamics, vol. 36, iss. 6, pp. 1797-1802, 2013.
R. Cole, M. J. Kochenderfer, R. E. Weibel, M. W. M. Edwards, D. J. Griffith, and W. A. Olson, “Fielding a sense and avoid capability for unmanned aircraft systems: policy, standards, technology, and safety modeling,” Air Traffic Control Quarterly, vol. 21, iss. 1, pp. 5-27, 2013.
J. E. Holland, M. J. Kochenderfer, and W. A. Olson, “Optimizing the next generation collision avoidance system for safe, suitable, and acceptable operational performance,” Air Traffic Control Quarterly, vol. 21, iss. 3, pp. 275-297, 2013.
J. E. Holland, M. J. Kochenderfer, and W. A. Olson, “Optimizing the next generation collision avoidance system for safe, suitable, and acceptable operational performance,” in Air Traffic Management Research and Development Seminar, Chicago, Illinois, 2013.
M. J. Kochenderfer and J. P. Chryssanthacopoulos, “Collision avoidance using partially controlled Markov decision processes,” in Agents and Artificial Intelligence, J. Filipe and A. Fred, Eds., Springer, 2013, vol. 271, pp. 86-100.
M. J. Kochenderfer and N. Monath, “Compression of optimal value functions for Markov decision processes,” in Data Compression Conference, Snowbird, Utah, 2013.
B. Puntin and M. J. Kochenderfer, “Traffic alert optimization for airborne collision avoidance systems,” in AIAA Guidance, Navigation, and Control Conference (GNC), Boston, Mass., 2013.
K. A. Smith, M. J. Kochenderfer, W. A. Olson, and A. E. Vela, “Collision avoidance system optimization for closely spaced parallel operations through surrogate modeling,” in AIAA Guidance, Navigation, and Control Conference (GNC), Boston, Mass., 2013.
A. J. Weinert, E. P. Harkleroad, D. J. Griffith, M. W. M. Edwards, and M. J. Kochenderfer, “Uncorrelated encounter model of the national airspace system version 2.0,” Massachusetts Institute of Technology, Lincoln Laboratory, Project Report ATC-404, 2013.
T. B. Billingsley, M. J. Kochenderfer, and J. P. Chryssanthacopoulos, “Collision avoidance for general aviation,” IEEE Aerospace and Electronic Systems Magazine, vol. 27, iss. 7, pp. 4-12, 2012.
J. P. Chryssanthacopoulos and M. J. Kochenderfer, “Decomposition methods for optimized collision avoidance with multiple threats,” Journal of Guidance, Control, and Dynamics, vol. 35, iss. 2, pp. 398-405, 2012.
J. P. Chryssanthacopoulos and M. J. Kochenderfer, “Hazard alerting based on probabilistic models,” Journal of Guidance, Control, and Dynamics, vol. 35, iss. 2, pp. 442-450, 2012.
M. J. Kochenderfer, J. P. Chryssanthacopoulos, and R. E. Weibel, “A new approach for designing safer collision avoidance systems,” Air Traffic Control Quarterly, vol. 20, iss. 1, pp. 27-45, 2012.
M. J. Kochenderfer, J. E. Holland, and J. P. Chryssanthacopoulos, “Next generation airborne collision avoidance system,” Lincoln Laboratory Journal, vol. 19, iss. 1, pp. 17-33, 2012.
E. J. Schlicht, R. Lee, D. H. Wolpert, M. J. Kochenderfer, and B. D. Tracey, “Predicting the behavior of interacting humans by fusing data from multiple sources,” in Conference on Uncertainty in Artificial Intelligence (UAI), Catalina Island, California, 2012.
H. Bai, D. Hsu, M. J. Kochenderfer, and W. S. Lee, “Unmanned aircraft collision avoidance using continuous-state POMDPs,” in Robotics: Science and Systems, 2011.
T. B. Billingsley, M. J. Kochenderfer, and J. P. Chryssanthacopoulos, “Collision avoidance for general aviation,” in Digital Avionics Systems Conference (DASC), Seattle, Washington, 2011.
J. P. Chryssanthacopoulos and M. J. Kochenderfer, “Collision avoidance system optimization with probabilistic pilot response models,” in American Control Conference (ACC), 2011.
J. P. Chryssanthacopoulos and M. J. Kochenderfer, “Decomposition methods for optimized collision avoidance with multiple threats,” in Digital Avionics Systems Conference (DASC), 2011.
J. P. Chryssanthacopoulos and M. J. Kochenderfer, “Hazard alerting based on probabilistic models,” in AIAA Guidance, Navigation, and Control Conference (GNC), Portland, Oregon, 2011.
J. P. Chryssanthacopoulos and M. J. Kochenderfer, “Analysis of open-loop and closed-loop planning for aircraft collision avoidance,” in IEEE International Conference on Intelligent Transportation Systems (ITSC), Washington, D.C., 2011.
J. P. Chryssanthacopoulos and M. J. Kochenderfer, “Accounting for state uncertainty in collision avoidance,” Journal of Guidance, Control, and Dynamics, vol. 34, iss. 4, pp. 951-960, 2011.
M. J. Kochenderfer and J. P. Chryssanthacopoulos, “Robust airborne collision avoidance through dynamic programming,” Massachusetts Institute of Technology, Lincoln Laboratory, Project Report ATC-371, 2011.
M. J. Kochenderfer and J. P. Chryssanthacopoulos, “Partially-controlled Markov decision processes for collision avoidance systems,” in International Conference on Agents and Artificial Intelligence, Rome, Italy, 2011.
M. J. Kochenderfer, J. P. Chryssanthacopoulos, and R. E. Weibel, “A new approach for designing safer collision avoidance systems,” in Air Traffic Management Research and Development Seminar, Berlin, Germany, 2011.
M. J. Kochenderfer, K. J. Shih, J. P. Chryssanthacopoulos, C. E. Rose, and T. R. Elder, “Position validation strategies using partially observable Markov decision processes,” in Digital Avionics Systems Conference (DASC), Seattle, Washington, 2011.
T. B. Wolf and M. J. Kochenderfer, “Aircraft collision avoidance using Monte Carlo real-time belief space search,” Journal of Intelligent and Robotic Systems, vol. 64, iss. 2, pp. 277-298, 2011.
J. P. Chryssanthacopoulos, M. J. Kochenderfer, and R. E. Williams, “Improved Monte Carlo sampling for conflict probability estimation,” in AIAA Non-Deterministic Approaches Conference, Orlando, Florida, 2010.
M. J. Kochenderfer, Adaptive Modelling and Planning: A computational approach for learning intelligent behaviour, LAP LAMBERT Academic Publishing, 2010.
M. J. Kochenderfer and J. P. Chryssanthacopoulos, “A decision-theoretic approach to developing robust collision avoidance logic,” in IEEE International Conference on Intelligent Transportation Systems (ITSC), Madeira Island, Portugal, 2010.
M. J. Kochenderfer, J. P. Chryssanthacopoulos, L. P. Kaelbling, T. Lozano-Perez, and J. K. Kuchar, “Model-based optimization of airborne collision avoidance logic,” Massachusetts Institute of Technology, Lincoln Laboratory, Project Report ATC-360, 2010.
M. J. Kochenderfer, J. P. Chryssanthacopoulos, and P. Radecki, “Robustness of optimized collision avoidance logic to modeling errors,” in Digital Avionics Systems Conference (DASC), Salt Lake City, Utah, 2010.
M. J. Kochenderfer, M. W. M. Edwards, L. P. Espindle, J. K. Kuchar, and D. J. Griffith, “Airspace encounter models for estimating collision risk,” Journal of Guidance, Control, and Dynamics, vol. 33, iss. 2, pp. 487-499, 2010.
M. J. Kochenderfer, D. J. Griffith, and J. E. Olszta, “On estimating mid-air collision risk,” in AIAA Aviation Technology, Integration, and Operations Conference, Fort Worth, Texas, 2010.
E. Maki, A. J. Weinert, and M. J. Kochenderfer, “Efficiently estimating ambient near mid-air collision risk for unmanned aircraft,” in AIAA Aviation Technology, Integration, and Operations Conference, Fort Worth, Texas, 2010.
S. Temizer, M. J. Kochenderfer, L. P. Kaelbling, T. Lozano-Perez, and J. K. Kuchar, “Collision avoidance for unmanned aircraft using Markov decision processes,” in AIAA Guidance, Navigation, and Control Conference (GNC), Toronto, Canada, 2010.
M. W. M. Edwards, M. J. Kochenderfer, J. K. Kuchar, and L. P. Espindle, “Encounter models for unconventional aircraft,” Massachusetts Institute of Technology, Lincoln Laboratory, Project Report ATC-348, 2009.
L. P. Espindle and M. J. Kochenderfer, “Classification of primary radar tracks using Gaussian mixture models,” IET Radar, Sonar and Navigation, vol. 3, iss. 6, pp. 559-568, 2009.
M. J. Kochenderfer, L. P. Espindle, M. W. M. Edwards, J. K. Kuchar, and D. J. Griffith, “Airspace encounter models for conventional and unconventional aircraft,” in Air Traffic Management Research and Development Seminar, Napa, Calif., 2009.
S. Temizer, M. J. Kochenderfer, L. P. Kaelbling, T. Lozano-Perez, and J. K. Kuchar, “Unmanned aircraft collision avoidance using partially observable Markov decision processes,” Massachusetts Institute of Technology, Lincoln Laboratory, Project Report ATC-356, 2009.
D. J. Griffith, M. J. Kochenderfer, and J. K. Kuchar, “Electro-optical system analysis for sense and avoid,” in AIAA Guidance, Navigation, and Control Conference (GNC), Honolulu, Hawaii, 2008.
M. J. Kochenderfer, L. P. Espindle, D. J. Griffith, and J. K. Kuchar, “Encounter modeling for sense and avoid development,” in Integrated Communications, Navigation and Surveillance Conference, Bethesda, Md., 2008.
M. J. Kochenderfer, L. P. Espindle, J. K. Kuchar, and D. J. Griffith, “Correlated encounter model for cooperative aircraft in the national airspace system,” Massachusetts Institute of Technology, Lincoln Laboratory, Project Report ATC-344, 2008.
M. J. Kochenderfer, L. P. Espindle, J. K. Kuchar, and D. J. Griffith, “A Bayesian approach to aircraft encounter modeling,” in AIAA Guidance, Navigation, and Control Conference (GNC), 2008.
M. J. Kochenderfer, L. P. Espindle, J. K. Kuchar, and D. J. Griffith, “A comprehensive aircraft encounter model of the national airspace system,” Lincoln Laboratory Journal, vol. 17, iss. 2, pp. 41-53, 2008.
M. J. Kochenderfer, D. J. Griffith, and J. K. Kuchar, “Hazard alerting using line-of-sight rate,” in AIAA Guidance, Navigation, and Control Conference (GNC), Honolulu, Hawaii, 2008.
M. J. Kochenderfer, J. K. Kuchar, L. P. Espindle, and D. J. Griffith, “Uncorrelated Encounter Model of the National Airspace System,” Massachusetts Institute of Technology, Lincoln Laboratory, Project Report ATC-345, 2008.
R. Gupta and M. J. Kochenderfer, “Systems and methods for using statistical techniques to reason with noisy data,” , iss. US 7,299,110 B2, 2007.
M. J. Kochenderfer, “Adaptive Abstraction for Model-Based Reinforcement Learning,” University of Edinburgh, School of Informatics, Technical Report EDI-INF-RR-0806, 2006.
M. J. Kochenderfer, “Adaptive Modelling and Planning for Learning Intelligent Behaviour,” PhD Thesis, University of Edinburgh, School of Informatics, 2006.
M. J. Kochenderfer, “Adaptive Modeling and Planning for Reactive Agents,” in AAAI Conference on Artificial Intelligence (AAAI), Pittsburgh, Pennsylvania, 2005.
M. J. Kochenderfer and G. Hayes, “Adaptive Partitioning of State Spaces using Decision Graphs for Real-Time Modeling and Planning,” in Workshop on Planning and Learning in A Priori Unknown or Dynamic Domains, International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, 2005.
M. J. Kochenderfer and G. Hayes, “Modeling and Planning in Large State and Action Spaces,” in Workshop on Planning and Learning in A Priori Unknown or Dynamic Domains, International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, 2005.
R. Gupta and M. J. Kochenderfer, “Common sense data acquisition for indoor mobile robots,” in AAAI Conference on Artificial Intelligence (AAAI), San Jose, Calif., 2004.
R. Gupta and M. J. Kochenderfer, “Using statistical techniques and WordNet to reason with noisy data,” in Workshop on Adaptive Text Extraction and Mining, AAAI Conference on Artificial Intelligence, San Jose, Calif., 2004.
M. J. Kochenderfer, “Evolving hierarchical and recursive teleo-reactive programs through genetic programming,” in European Conference on Genetic Programming, Essex, England, 2003, pp. 84-94.
M. J. Kochenderfer and R. Gupta, “Common sense data acquisition for indoor mobile robots,” in Distributed and Collaborative Knowledge Capture Workshop, International Conference on Knowledge Capture, Sanibel, Fla., 2003.
M. J. Kochenderfer, “Evolving teleo-reactive programs for block stacking using indexicals through genetic programming,” in Genetic Algorithms and Genetic Programming at Stanford, Stanford, Calif., 2002, pp. 111-118.

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