Mehdi Fatemi
Mehdi Fatemi
Microsoft Research
Verified email at - Homepage
Cited by
Cited by
Cognitive Control
S Haykin, M Fatemi, P Setoodeh, Y Xue
IEEE, 2012
Hybrid reward architecture for reinforcement learning
H Van Seijen, M Fatemi, J Romoff, R Laroche, T Barnes, J Tsang
arXiv preprint arXiv:1706.04208, 2017
Policy networks with two-stage training for dialogue systems
M Fatemi, LE Asri, H Schulz, J He, K Suleman
arXiv preprint arXiv:1606.03152, 2016
Cognitive control: Theory and application
M Fatemi, S Haykin
IEEE Access 2, 698-710, 2014
Multi-advisor reinforcement learning
R Laroche, M Fatemi, J Romoff, H van Seijen
arXiv preprint arXiv:1704.00756, 2017
Separation of concerns in reinforcement learning
H van Seijen, M Fatemi, J Romoff, R Laroche
arXiv preprint arXiv:1612.05159, 2016
Observability of stochastic complex networks under the supervision of cognitive dynamic systems
M Fatemi, P Setoodeh, S Haykin
Journal of Complex Networks 5 (3), 433-460, 2017
Using a logarithmic mapping to enable lower discount factors in reinforcement learning
H Van Seijen, M Fatemi, A Tavakoli
Advances in Neural Information Processing Systems 32, 14134-14144, 2019
Cognitive control in cognitive dynamic systems: A new way of thinking inspired by the brain
S Haykin, A Amiri, M Fatemi
2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement …, 2014
An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare
TW Killian, H Zhang, J Subramanian, M Fatemi, M Ghassemi
arXiv preprint arXiv:2011.11235, 2020
Discrete event control of an unmanned aircraft
M Fatemi, J Millan, J Stevenson, T Yu, S O'Young
2008 9th International Workshop on Discrete Event Systems, 352-357, 2008
Post-training on RBF neural networks
F Shabaninia, M Roopaei, M Fatemi
Nonlinear Analysis: Hybrid Systems 1 (4), 491-500, 2007
Dead-ends and Secure Exploration in Reinforcement Learning
M Fatemi, S Sharma, H Van Seijen, SE Kahou
International Conference on Machine Learning, 1873-1881, 2019
New Training Methods for RBF Neural Networks
M Fatemi, M Roopaei, F Shabaninia
2005 International Conference on Neural Networks and Brain 3, 1322-1327, 2005
Learning to represent action values as a hypergraph on the action vertices
A Tavakoli, M Fatemi, P Kormushev
arXiv preprint arXiv:2010.14680, 2020
Medical Dead-ends and Learning to Identify High-risk States and Treatments
M Fatemi, TW Killian, J Subramanian, M Ghassemi
Advances in Neural Information Processing Systems 34, 2021
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
S Sohn, S Lee, J Choi, H van Seijen, M Fatemi, H Lee
arXiv preprint arXiv:2107.06405, 2021
About the attractor phenomenon in decomposed reinforcement learning
R Laroche, M Fatemi, J Romoff, H van Seijen
Toward a general control design paradigm for hybrid systems: Ideas, concepts, and formulations
M Fatemi, J Millan, T Yu, S O'Young
2009 Canadian Conference on Electrical and Computer Engineering, 1158-1162, 2009
Unmanned Aerial Vehicles:“Sense and Avoid” Problem
M Fatemi, J Millan, J Stevenson, S O’Young, T Yu
IEEE Newfoundland and Labrador, 180 Portugal Road, Holiday Inn, St. John's …, 2008
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