Ishan Durugkar

According to our database, Ishan Durugkar authored at least 21 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences.

Siddhant Agarwal, Ishan Durugkar, Peter Stone, Amy Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DM²: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching.

Caroline Wang, Ishan Durugkar, Elad Liebman, Peter Stone

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

ABC: Adversarial Behavioral Cloning for Offline Mode-Seeking Imitation Learning.

Eddy Hudson, Ishan Durugkar, Garrett Warnell, Peter Stone

CoRR, 2022

DM²: Distributed Multi-Agent Reinforcement Learning for Distribution Matching.

Caroline Wang, Ishan Durugkar, Elad Liebman, Peter Stone

CoRR, 2022

Towards a Real-Time, Low-Resource, End-to-End Object Detection Pipeline for Robot Soccer.

Sai Kiran Narayanaswami, Mauricio Tec, Ishan Durugkar, Siddharth Desai, Bharath Masetty, Sanmit Narvekar, Peter Stone

Proceedings of the RoboCup 2022:, 2022

2021

Wasserstein Distance Maximizing Intrinsic Control.

Ishan Durugkar, Steven Hansen, Stephen Spencer, Volodymyr Mnih

CoRR, 2021

Adversarial Intrinsic Motivation for Reinforcement Learning.

Ishan Durugkar, Mauricio Tec, Scott Niekum, Peter Stone

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

An Imitation from Observation Approach to Sim-to-Real Transfer.

Siddharth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, Peter Stone

CoRR, 2020

An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch.

Siddharth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, Peter Stone

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning.

Ishan Durugkar, Elad Liebman, Peter Stone

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Reducing Sampling Error in Batch Temporal Difference Learning.

Brahma S. Pavse, Ishan Durugkar, Josiah Hanna, Peter Stone

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Multi-Preference Actor Critic.

Ishan Durugkar, Matthew J. Hausknecht, Adith Swaminathan, Patrick MacAlpine

CoRR, 2019

2018

Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning.

Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Akshay Krishnamurthy, Alex Smola, Andrew McCallum

Proceedings of the 6th International Conference on Learning Representations, 2018

Adversarial Goal Generation for Intrinsic Motivation.

Ishan Durugkar, Peter Stone

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Unmixing in the presence of nuisances with deep generative models.

Mario Parente, Ian Gemp, Ishan P. Durugkar

Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017

Generative Multi-Adversarial Networks.

Ishan P. Durugkar, Ian Gemp, Sridhar Mahadevan

Proceedings of the 5th International Conference on Learning Representations, 2017

Go for a Walk and Arrive at the Answer: Reasoning Over Knowledge Bases with Reinforcement Learning.

Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Akshay Krishnamurthy, Alex Smola, Andrew McCallum

Proceedings of the 6th Workshop on Automated Knowledge Base Construction, 2017

Predictive Off-Policy Policy Evaluation for Nonstationary Decision Problems, with Applications to Digital Marketing.

Philip S. Thomas, Georgios Theocharous, Mohammad Ghavamzadeh, Ishan Durugkar, Emma Brunskill

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Deep Generative Models for Spectroscopic Analysis on Mars.

Ian Gemp, Ishan P. Durugkar, Mario Parente, Melinda Darby Dyar, Sridhar Mahadevan

CoRR, 2016

Deep Reinforcement Learning With Macro-Actions.

Ishan P. Durugkar, Clemens Rosenbaum, Stefan Dernbach, Sridhar Mahadevan

CoRR, 2016

2013

Cohort Intelligence: A Self Supervised Learning Behavior.

Anand J. Kulkarni, Ishan P. Durugkar, Mrinal Kumar

Proceedings of the IEEE International Conference on Systems, 2013