Grant: Postgraduate Scholarships - Doctoral
New York University
$21,000.00
The use of memory mechanism for long horizon, partially observable credit assignment in reinforcement learning
EF 2022-23
Résumé
Machine learning, Reinforcement learning, Deep learning, Memory, Partial observability, Attention mechanisms, Neuroscience, Recurrent neural networks
Programme
Postgraduate Scholarships - Doctoral
Bénéficiaire
Emplacement
New York, UNITED STATES
Type de bénéficiaire
Not-for-profit organization or charity
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
559278-2021
Name nom
CHEN, ANTHONY GUANXUN AGX
Department département
Computer Science
Organization id
1442
Institution établissement
New York University
Province en
New York
Province fr
New York
Country en
UNITED STATES
Country fr
ÉTATS-UNIS
Fiscal year exercice financier
2022
Competition year année de concours
2021
Award amount
21000
Program id
PGSD
Program name en
Postgraduate Scholarships - Doctoral
Program name fr
Bourses d'études supérieures - doctorat
Group en
RESEARCH TRAINING AND TALENT DEVELOPMENT
Group fr
FORMATION EN RECHERCHE ET PERFECTIONNEMENT DES COM
Committee code
198
Committee name en
S&F Committee for Computing Sciences
Committee name fr
Comité de sélection des bourses en informatique
Area of application code
9999
Area of application group en
Not available
Area of application group fr
Non disponible
Area of application en
Not available
Area of application fr
Non disponible
Research subject code
2800
Research subject group en
Artificial intelligence
Research subject group fr
Intelligence artificielle
Research subject en
Artificial intelligence (computer vision, use2603)
Research subject fr
Intelligence artificielle (vision artificielle, utiliser 2603)
Installment
inst:4;5
Partie
2
Nb partie
5
Application title
The use of memory mechanism for long horizon, partially observable credit assignment in reinforcement learning
Application summary
Machine learning, Reinforcement learning, Deep learning, Memory, Partial observability, Attention mechanisms, Neuroscience, Recurrent neural networks
