Curriculum learning improves compositionality of reinforcement learning agent across concept classes

Curriculum learning improves compositionality of reinforcement learning agent across concept classes

The compositional structure afforded by language allows humans to decompose complex phrases and map them to novel visual concepts, demonstrating flexible intelligence. Although there have been several algorithms that can demonstrate compositionality, they do not give us insights on how humans learn...

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書目詳細資料
主要作者:	Lin, Zijun
其他作者:	Wen Bihan
格式:	Final Year Project
語言:	English
出版:	Nanyang Technological University 2024
主題:	Computer and Information Science Reinforcement learning
在線閱讀:	https://hdl.handle.net/10356/176294
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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