Ishan Durugkar
Ishan Durugkar
Research Scientist, Sony AI
Verified email at - Homepage
Cited by
Cited by
Go for a walk and arrive at the answer: Reasoning over paths in knowledge bases using reinforcement learning
R Das, S Dhuliawala, M Zaheer, L Vilnis, I Durugkar, A Krishnamurthy, ...
arXiv preprint arXiv:1711.05851, 2017
Generative Multi-Adversarial Networks
I Durugkar, I Gemp, S Mahadevan
International Conference on Learning Representations, 2017, 2017
Cohort intelligence: a self supervised learning behavior
AJ Kulkarni, IP Durugkar, M Kumar
2013 IEEE international conference on systems, man, and cybernetics, 1396-1400, 2013
Predictive off-policy policy evaluation for nonstationary decision problems, with applications to digital marketing
P Thomas, G Theocharous, M Ghavamzadeh, I Durugkar, E Brunskill
Proceedings of the AAAI Conference on Artificial Intelligence 31 (2), 4740-4745, 2017
An imitation from observation approach to transfer learning with dynamics mismatch
S Desai, I Durugkar, H Karnan, G Warnell, J Hanna, P Stone
Advances in Neural Information Processing Systems 33, 3917-3929, 2020
Adversarial intrinsic motivation for reinforcement learning
I Durugkar, M Tec, S Niekum, P Stone
Advances in Neural Information Processing Systems 34, 8622-8636, 2021
Deep reinforcement learning with macro-actions
IP Durugkar, C Rosenbaum, S Dernbach, S Mahadevan
arXiv preprint arXiv:1606.04615, 2016
Balancing individual preferences and shared objectives in multiagent reinforcement learning
I Durugkar, E Liebman, P Stone
International Joint Conference on Artificial Intelligence, 2020
Reducing sampling error in batch temporal difference learning
B Pavse, I Durugkar, J Hanna, P Stone
International Conference on Machine Learning, 7543-7552, 2020
TD learning with constrained gradients
I Durugkar, P Stone
Towards a real-time, low-resource, end-to-end object detection pipeline for robot soccer
SK Narayanaswami, M Tec, I Durugkar, S Desai, B Masetty, S Narvekar, ...
Robot World Cup, 62-74, 2022
Wasserstein distance maximizing intrinsic control
I Durugkar, S Hansen, S Spencer, V Mnih
arXiv preprint arXiv:2110.15331, 2021
Unmixing in the presence of nuisances with deep generative models
M Parente, I Gemp, I Durugkar
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2017
An imitation from observation approach to sim-to-real transfer
S Desai, I Durugkar, H Karnan, G Warnell, J Hanna, P Stone, A Sony
2nd Workshop on Closing the Reality Gap in Sim2Real Transfer for Robotics. RSS, 2020
ABC: Adversarial Behavioral Cloning for Offline Mode-Seeking Imitation Learning
E Hudson, I Durugkar, G Warnell, P Stone
arXiv preprint arXiv:2211.04005, 2022
DM : Distributed multi-agent reinforcement learning via distribution matching
C Wang
Multi-preference actor critic
I Durugkar, M Hausknecht, A Swaminathan, P MacAlpine
arXiv preprint arXiv:1904.03295, 2019
Inverting variational autoencoders for improved generative accuracy
I Gemp, I Durugkar, M Parente, MD Dyar, S Mahadevan
arXiv preprint arXiv:1608.05983, 2016
f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences
S Agarwal, I Durugkar, P Stone, A Zhang
Advances in Neural Information Processing Systems 36, 2024
Estimation and control of visitation distributions for reinforcement learning
I Durugkar
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