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In open-world environments like Minecraft, existing agents face challenges in continuously learning structured knowledge, particularly causality.
Learning neural causal models from unknown interventions
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The minerl 2019 competition on sample efficient reinforcement learning using human priors
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Zhu, S., Ng, I., and Chen, Z · 2019
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Lin, Z., Li, J., Shi, J., Ye, D., Fu, Q., and Yang, W · 2021
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Learning transferable visual models from natural language supervision
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Open-ended learning leads to generally capable agents
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Liu, H., Li, C., Wu, Q., and Lee, Y. J · 2024
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Toolformer: Language models can teach themselves to use tools
Schick, T., Dwivedi-Yu, J., Dessì, R., Raileanu, R., Lomeli, M., Hambro, E., Zettlemoyer, L., Cancedda, N., and Scialom, T · 2024
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Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face
Shen, Y., Song, K., Tan, X., Li, D., Lu, W., and Zhuang, Y · 2024
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Reflexion: Language agents with verbal reinforcement learning
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Causal-learn: Causal discovery in python
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