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Found 14 papers, 2 papers with code
Learning to Guide Multiple Heterogeneous Actors from a Single Human Demonstration via Automatic Curriculum Learning in StarCraft II
Traditionally, learning from human demonstrations via direct behavior cloning can lead to high-performance policies given that the algorithm has access to large amounts of high-quality data covering the most likely scenarios to be encountered when the agent is operating.
On games and simulators as a platform for development of artificial intelligence for command and control
Games and simulators can be a valuable platform to execute complex multi-agent, multiplayer, imperfect information scenarios with significant parallels to military applications: multiple participants manage resources and make decisions that command assets to secure specific areas of a map or neutralize opposing forces.
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models.
SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing
We perform a validation experiment of NMT on English-Japanese machine translation, and find that it is possible to achieve comparable accuracy to direct subword training from raw sentences.
A Japanese Chess Commentary Corpus
We describe a detailed definition of named entities and show some statistics of our game commentary corpus.
Bilingual Dictionary Construction with Transliteration Filtering
In this paper we present a bilingual transliteration lexicon of 170K Japanese-English technical terms in the scientific domain.
