Beomjoon Kim
TitleCited byYear
Socially adaptive path planning in human environments using inverse reinforcement learning
B Kim, J Pineau
International Journal of Social Robotics 8 (1), 51-66, 2016
752016
Learning from limited demonstrations
B Kim, A Farahmand, J Pineau, D Precup
Advances in Neural Information Processing Systems, 2859-2867, 2013
472013
Maximum Mean Discrepancy Imitation Learning
B Kim, J Pineau
Robotics: Science and Systems, 2013
242013
Learning to guide task and motion planning using score-space representation
B Kim, Z Wang, LP Kaebling, T Lozano-Perez
The International Journal of Robotics Research 28 (7), 2019
142019
Learning to guide task and motion planning using score-space representation
B Kim, LP Kaelbling, T Lozano-Pérez
142017
Human-like navigation: Socially adaptive path planning in dynamic environments
B Kim, J Pineau
RSS 2013 Workshop on Inverse Optimal Control and Robotic Learning from …, 2013
92013
Guiding Search in Continuous State-action Spaces by Learning an Action Sampler from Off-target Search Experience
B Kim, LP Kaelbling, T Lozano-Pérez
AAAI Conference on Artificial Intelligence, 2018
72018
Generalizing over uncertain dynamics for online trajectory generation
B Kim, A Kim, H Dai, L Kaelbling, T Lozano-Perez
Robotics Research, 39-55, 2018
52018
Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior
Z Wang, B Kim, LP Kaelbling
Advances in Neural Information Processing Systems, 10477-10488, 2018
42018
Adversarial Actor-Critic Method for Task and Motion Planning Problems Using Planning Experience
B Kim, LP Kaelbling, T Lozano-Pérez
22019
An optimisation model for airlift load planning: GALAHAD and the quest for the ‘holy grail’
BL Kaluzny, RHAD Shaw, A Ghanmi, B Kim
2009 IEEE Symposium on Computational Intelligence for Security and Defense …, 2009
12009
Guiding the search in continuous state-action spaces by learning an action sampling distribution from off-target samples
B Kim, LP Kaelbling, T Lozano-Perez
arXiv preprint arXiv:1711.01391, 2017
2017
Efficient Imitation Learning and Inverse Reinforcement Learning with Application to Navigation in Human Environments
B Kim
McGill University Libraries, 2014
2014
Approximate Policy Iteration with Demonstration Data
B Kim, A Farahmand, J Pineau, D Precup
RLDM 2013, 168, 2013
2013
Learning value functions with relational state representations for guiding task-and-motion planning
B Kim, L Shimanuki
Learning from Limited Demonstrations: Proof of Theorem
B Kim
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Articles 1–16