Dong Ki Kim
Dong Ki Kim
Research Scientist, LG AI Research (previously: MIT)
Verified email at - Homepage
Cited by
Cited by
Deep neural network for real-time autonomous indoor navigation
DK Kim, T Chen
arXiv preprint arXiv:1511.04668, 2015
Learning to teach in cooperative multiagent reinforcement learning
S Omidshafiei, DK Kim, M Liu, G Tesauro, M Riemer, C Amato, ...
AAAI 2019, Best Student Paper Honorable Mention 33, 6128-6136, 2019
Satellite image-based localization via learned embeddings
DK Kim, MR Walter
IEEE International Conference on Robotics and Automation (ICRA), 2073-2080, 2017
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
DK Kim, M Liu, M Riemer, C Sun, M Abdulhai, G Habibi, S Lopez-Cot, ...
International Conference on Machine Learning (ICML), 5541-5550, 2021
Learning hierarchical teaching policies for cooperative agents
DK Kim, M Liu, S Omidshafiei, S Lopez-Cot, M Riemer, G Habibi, ...
arXiv preprint arXiv:1903.03216 (Accepted to AAMAS 2020), 2019
Season-invariant semantic segmentation with a deep multimodal network
DK Kim, D Maturana, M Uenoyama, S Scherer
Field and service robotics (FSR), 255-270, 2018
You are here: Mimicking the human thinking process in reading floor-plans
H Chu, DK Kim, T Chen
International Conference on Computer Vision (ICCV), 2210-2218, 2015
Policy distillation and value matching in multiagent reinforcement learning
S Wadhwania, DK Kim, S Omidshafiei, JP How
International Conference on Intelligent Robots and Systems (IROS), 8193-8200, 2019
Influencing long-term behavior in multiagent reinforcement learning
DK Kim, M Riemer, M Liu, J Foerster, M Everett, C Sun, G Tesauro, ...
Advances in Neural Information Processing Systems 35, 18808-18821, 2022
Efficient guided policy search via imitation of robust tube MPC
A Tagliabue, DK Kim, M Everett, JP How
International Conference on Robotics and Automation (ICRA), 462-468, 2022
Romax: Certifiably robust deep multiagent reinforcement learning via convex relaxation
C Sun, DK Kim, JP How
International Conference on Robotics and Automation (ICRA), 5503-5510, 2022
Crossmodal attentive skill learner
S Omidshafiei, DK Kim, J Pazis, JP How
International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), 2017
City-wide street-to-satellite image geolocalization of a mobile ground agent
LM Downes, DK Kim, TJ Steiner, JP How
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS …, 2022
Context-specific representation abstraction for deep option learning
M Abdulhai, DK Kim, M Riemer, M Liu, G Tesauro, JP How
Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 5959-5967, 2022
FISAR: Forward Invariant Safe Reinforcement Learning with a Deep Neural Network-Based Optimize
C Sun, DK Kim, JP How
IEEE International Conference on Robotics and Automation (ICRA), 10617-10624, 2021
Game-Theoretical Perspectives on Active Equilibria: A Preferred Solution Concept over Nash Equilibria
DK Kim, M Riemer, M Liu, JN Foerster, G Tesauro, JP How
arXiv preprint arXiv:2210.16175 (Accepted to CoRL Strategic Multi-Agent …, 2022
Code Models are Zero-shot Precondition Reasoners
L Logeswaran, S Sohn, Y Lyu, AZ Liu, DK Kim, D Shim, M Lee, H Lee
arXiv preprint arXiv:2311.09601, 2023
Multiagent Reinforcement Learning
JP How, DK Kim, S Wadhwania
Encyclopedia of Systems and Control, 1359-1367, 2021
Online Semantic Mapping for Autonomous Navigation and Scouting
D Maturana, S Arora, P Chou, D Kim, M Uenoyama, S Scherer
TOD-Flow: Modeling the Structure of Task-Oriented Dialogues
S Sohn, Y Lyu, A Liu, L Logeswaran, DK Kim, D Shim, H Lee
arXiv preprint arXiv:2312.04668 (EMNLP 2023), 2023
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