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Aakriti Agrawal
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Parameter sharing for heterogeneous agents in multi-agent reinforcement learning
JK Terry, N Grammel, S Son, B Black, A Aakriti
arXiv preprint arXiv:2005.13625, 2020
120*2020
Rtaw: An attention inspired reinforcement learning method for multi-robot task allocation in warehouse environments
A Agrawal, AS Bedi, D Manocha
2023 IEEE International Conference on Robotics and Automation (ICRA), 1393-1399, 2023
72023
Mid-flight propeller failure detection and control of propeller-deficient quadcopter using reinforcement learning
R Arasanipalai, A Agrawal, D Ghose
arXiv preprint arXiv:2002.11564, 2020
72020
Dc-mrta: Decentralized multi-robot task allocation and navigation in complex environments
A Agrawal, S Hariharan, AS Bedi, D Manocha
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022
52022
Benchmarking the Robustness of Image Watermarks
B An, M Ding, T Rabbani, A Agrawal, Y Xu, C Deng, S Zhu, A Mohamed, ...
arXiv preprint arXiv:2401.08573, 2024
12024
Robustness to Multi-Modal Environment Uncertainty in MARL using Curriculum Learning
A Agrawal, R Aralikatti, Y Sun, F Huang
https://arxiv.org/abs/2310.08746, 2023
2023
Learning when to trust which teacher for weakly supervised ASR
A Agrawal, M Rao, AK Sahu, G Chennupati, A Stolcke
arXiv preprint arXiv:2306.12012, 2023
2023
Accurate Estimation of 3D-Repetitive-Trajectories using Kalman Filter, Machine Learning and Curve-Fitting Method for High-speed Target Interception
A Agrawal, A Bhise, R Arasanipalai, LA Tony, S Jana, D Ghose
Artificial Intelligence for Robotics and Autonomous Systems Applications, 93-122, 2023
2023
Least Squares curve fitting and RNN-based trajectory estimation for noisy looping trajectories
A Aakriti, A Rohitkumar, G Debasish
MBZIRC 2020 Symposium, 2020
2020
A Comparative Study of Noise Cancellation Using Least Mean Squares Adaptive Filter and Recurrent Neural Network Filter
A Agrawal, R Arasanipalai, B Sainath
2018 2nd International Conference on Power, Energy and Environment: Towards …, 2018
2018
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Articles 1–10