3 papers
cs.MA2020
Resolving Implicit Coordination in Multi-Agent Deep Reinforcement Learning with Deep Q-Networks & Game Theory
Griffin Adams, Sarguna Janani Padmanabhan, Shivang Shekhar
We address two major challenges of implicit coordination in multi-agent deep reinforcement learning: non-stationarity and exponential growth of state-action space, by combining Dee…
cs.CL2018
When and Why are Pre-trained Word Embeddings Useful for Neural Machine Translation?
Ye Qi, Devendra Singh Sachan, Matthieu Felix +2
The performance of Neural Machine Translation (NMT) systems often suffers in low-resource scenarios where sufficiently large-scale parallel corpora cannot be obtained. Pre-trained…
cs.CL2018
XNMT: The eXtensible Neural Machine Translation Toolkit
Graham Neubig, Matthias Sperber, Xinyi Wang +10
This paper describes XNMT, the eXtensible Neural Machine Translation toolkit. XNMT distin- guishes itself from other open-source NMT toolkits by its focus on modular code design, w…