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pro vyhledávání: '"Loynd, Ricky"'
Autor:
Thomas, Garrett, Cheng, Ching-An, Loynd, Ricky, Frujeri, Felipe Vieira, Vineet, Vibhav, Jalobeanu, Mihai, Kolobov, Andrey
A rich representation is key to general robotic manipulation, but existing approaches to representation learning require large amounts of multimodal demonstrations. In this work we propose PLEX, a transformer-based architecture that learns from a sma
Externí odkaz:
http://arxiv.org/abs/2303.08789
Autor:
Diao, Cameron, Loynd, Ricky
Transformers flexibly operate over sets of real-valued vectors representing task-specific entities and their attributes, where each vector might encode one word-piece token and its position in a sequence, or some piece of information that carries no
Externí odkaz:
http://arxiv.org/abs/2210.05062
Autor:
Wagener, Nolan, Kolobov, Andrey, Frujeri, Felipe Vieira, Loynd, Ricky, Cheng, Ching-An, Hausknecht, Matthew
Simulated humanoids are an appealing research domain due to their physical capabilities. Nonetheless, they are also challenging to control, as a policy must drive an unstable, discontinuous, and high-dimensional physical system. One widely studied ap
Externí odkaz:
http://arxiv.org/abs/2208.07363
Transformers have increasingly outperformed gated RNNs in obtaining new state-of-the-art results on supervised tasks involving text sequences. Inspired by this trend, we study the question of how Transformer-based models can improve the performance o
Externí odkaz:
http://arxiv.org/abs/1911.07141
Interactive Fiction (IF) games are complex textual decision making problems. This paper introduces NAIL, an autonomous agent for general parser-based IF games. NAIL won the 2018 Text Adventure AI Competition, where it was evaluated on twenty unseen g
Externí odkaz:
http://arxiv.org/abs/1902.04259
Publikováno v:
Proceedings of the 7th ACM International Conference Web Search & Data Mining; 2/24/2014, p453-462, 10p