Fetching the paper…
Reading the bibliography…
Theory of games and economic behavior
John Von Neumann and Oskar Morgenstern. 1945 · 1945
Earlier work this paper cites.
Stimulus and response generalization: A stochastic model relating generalization to distance in psychological space
Roger N. Shepard. 1957 · 1957
Earlier work this paper cites.
Individual choice behavior
R. Duncan Luce. 1959 · 1959
Earlier work this paper cites.
The American Economic Review 50, 1 (1960), 186–188
Gerard Debreu. 1960 · 1960
Earlier work this paper cites.
Structure of Passenger Travel Demand Models
Moshe Ben-Akiva. 1973 · 1973
Earlier work this paper cites.
The choice axiom after twenty years
R.Duncan Luce. 1977 · 1977
Earlier work this paper cites.
Application of Cross-Nested Logit Model to Mode Choice in Tel Aviv, Israel, Metropolitan Area
Peter Vovsha. 1997 · 1997
Earlier work this paper cites.
Goal inference as inverse planning
Chris Baker, Joshua B Tenenbaum, and Rebecca R Saxe. 2007 · 2007
Earlier work this paper cites.
Bayesian Inverse Reinforcement Learning. In Proceedings of the 20th International Joint Conference on Artifical Intelligence (IJCAI’07) . Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 2586–2591
Deepak Ramachandran and Eyal Amir. 2007 · 2007
Earlier work this paper cites.
Maximum Entropy Inverse Reinforcement Learning. In Proceedings of the 23rd National Conference on Artificial Intelligence - Volume 3 (AAAI’08) . AAAI Press, 1433–1438
Brian D. Ziebart, Andrew Maas, J. Andrew Bagnell, and Anind K. Dey. 2008 · 2008
Cited alongside, same era.
Brian D. Ziebart, Nathan Ratliff, Garratt Gallagher, Christoph Mertz, Kevin Peterson, J. Andrew Bagnell, Martial Hebert, Anind K. Dey, and Siddhartha Srinivasa. 2009 · 2009
Cited alongside, same era.
Learning to navigate through crowded environments. In 2010 IEEE International Conference on Robotics and Automation . 981–986
P. Henry, C. Vollmer, B. Ferris, and D. Fox. 2010 · 2010
Cited alongside, same era.
Testing statistical hypotheses of equivalence and noninferiority
Stefan Wellek. 2010 · 2010
Cited alongside, same era.
Random Choice as Behavioral Optimization
Faruk Gul, Paulo Natenzon, and Wolfgang Pesendorfer. 2014 · 2014
Later among the works it cites.
Inverse Reinforcement Learning algorithms and features for robot navigation in crowds: An experimental comparison. In 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems . 1341–1346
D. Vasquez, B. Okal, and K. O. Arras. 2014 · 2014
Later among the works it cites.
Predicting human reaching motion in collaborative tasks using Inverse Optimal Control and iterative re-planning. In 2015 IEEE International Conference on Robotics and Automation (ICRA) . 885–892
J. Mainprice, R. Hayne, and D. Berenson. 2015 · 2015
Later among the works it cites.
Maximum Entropy Deep Inverse Reinforcement Learning
Markus Wulfmeier, Peter Ondruska, and Ingmar Posner. 2015 · 2015
Later among the works it cites.
Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization. In Proceedings of the 33rd International Conference on International Conference on Machine Learning - Volume 48 (ICML’16) . JMLR.org, 49–58
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Maximum entropy inverse reinforcement learning in continuous state spaces with path integrals. In 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems . 1561–1566
N. Aghasadeghi and T. Bretl. 2011 · 2011
Cited alongside, same era.
Activity Forecasting. In Computer Vision – ECCV 2012 , Andrew Fitzgibbon, Svetlana Lazebnik, Pietro Perona, Yoichi Sato, and Cordelia Schmid (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 201–214
Kris M. Kitani, Brian D. Ziebart, James Andrew Bagnell, and Martial Hebert. 2012 · 2012
Cited alongside, same era.
Continuous Inverse Optimal Control with Locally Optimal Examples. In Proceedings of the 29th International Coference on International Conference on Machine Learning (ICML’12) . Omnipress, USA, 475–482
Sergey Levine and Vladlen Koltun. 2012 · 2012
Cited alongside, same era.
Learning objective functions for manipulation. In 2013 IEEE International Conference on Robotics and Automation . 1331–1336
M. Kalakrishnan, P. Pastor, L. Righetti, and S. Schaal. 2013 · 2013
Cited alongside, same era.
Human-robot collaborative manipulation planning using early prediction of human motion. In 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems . 299–306
J. Mainprice and D. Berenson. 2013 · 2013
Cited alongside, same era.
Chelsea Finn, Sergey Levine, and Pieter Abbeel. 2016 · 2016
Later among the works it cites.
psiTurk: An open-source framework for conducting replicable behavioral experiments online
Todd M. Gureckis, Jay Martin, John McDonnell, Alexander S. Rich, Doug Markant, Anna Coenen, David Halpern, Jessica B. Hamrick, and Patricia Chan. 2016 · 2016
Later among the works it cites.
Socially Compliant Mobile Robot Navigation via Inverse Reinforcement Learning
Henrik Kretzschmar, Markus Spies, Christoph Sprunk, and Wolfram Burgard. 2016 · 2016
Later among the works it cites.
Predicting actions to act predictably: Cooperative partial motion planning with maximum entropy models. In 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . 2096–2101
M. Pfeiffer, U. Schwesinger, H. Sommer, E. Galceran, and R. Siegwart. 2016 · 2016
Later among the works it cites.
Learning under Misspecified Objective Spaces. In CoRL
Andreea Bobu, Andrea Bajcsy, Jaime F. Fisac, and Anca D. Dragan. 2018 · 2018
Later among the works it cites.