Joshua Romoff
Joshua Romoff
Geverifieerd e-mailadres voor mail.mcgill.ca
TitelGeciteerd doorJaar
Hybrid reward architecture for reinforcement learning
H Van Seijen, M Fatemi, J Romoff, R Laroche, T Barnes, J Tsang
Advances in Neural Information Processing Systems, 5392-5402, 2017
572017
Multi-advisor reinforcement learning
R Laroche, M Fatemi, J Romoff, H van Seijen
arXiv preprint arXiv:1704.00756, 2017
92017
Randomized value functions via multiplicative normalizing flows
A Touati, H Satija, J Romoff, J Pineau, P Vincent
arXiv preprint arXiv:1806.02315, 2018
62018
Separation of concerns in reinforcement learning
H van Seijen, M Fatemi, J Romoff, R Laroche
arXiv preprint arXiv:1612.05159, 2016
6*2016
Deep conditional multi-task learning in atari
J Romoff, E Bengio, J Pineau
ICML 48, 2016
32016
TarMAC: Targeted Multi-Agent Communication
A Das, T Gervet, J Romoff, D Batra, D Parikh, M Rabbat, J Pineau
arXiv preprint arXiv:1810.11187, 2018
22018
Where did my optimum go?: An empirical analysis of gradient descent optimization in policy gradient methods
P Henderson, J Romoff, J Pineau
arXiv preprint arXiv:1810.02525, 2018
22018
Reward estimation for variance reduction in deep reinforcement learning
J Romoff, A Piché, P Henderson, V Francois-Lavet, J Pineau
arXiv preprint arXiv:1805.03359, 2018
22018
Separating value functions across time-scales
J Romoff, P Henderson, A Touati, Y Ollivier, E Brunskill, J Pineau
arXiv preprint arXiv:1902.01883, 2019
12019
Scalability of reinforcement learning by separation of concerns
HH Van Seijen, SMF Booshehri, RMH Laroche, JS Romoff
US Patent App. 15/634,811, 2018
2018
Hybrid reward architecture for reinforcement learning
HH Van Seijen, SMF Booshehri, RMH Laroche, JS Romoff
US Patent App. 15/634,914, 2018
2018
About the attractor phenomenon in decomposed reinforcement learning
R Laroche, M Fatemi, J Romoff, H van Seijen
2018
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Artikelen 1–12