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Too many cooks: Coordinating multi-agent collaboration through inverse planning.

, , , , , and . CogSci, cognitivesciencesociety.org, (2020)

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Know Thy Student: Interactive Learning with Gaussian Processes., , and . CoRR, (2022)Too Many cooks: Bayesian inference for coordinating Multi-agent Collaboration., , , , , and . Human-Like Machine Intelligence, Oxford University Press, (2022)Step-by-Step Remediation of Students' Mathematical Mistakes., , , , and . CoRR, (2023)Model-based Reinforcement Learning for Decentralized Multiagent Rendezvous., , , , , , , and . CoRL, volume 155 of Proceedings of Machine Learning Research, page 711-725. PMLR, (2020)Cooperation without Coordination: Hierarchical Predictive Planning for Decentralized Multiagent Navigation., , , , , , , and . CoRR, (2020)Calibrate your listeners! Robust communication-based training for pragmatic speakers., , , and . EMNLP (Findings), page 977-984. Association for Computational Linguistics, (2021)Too many cooks: Coordinating multi-agent collaboration through inverse planning., , , , , and . CogSci, cognitivesciencesociety.org, (2020)Evaluating Human-Language Model Interaction., , , , , , , , , and 8 other author(s). CoRR, (2022)Is ChatGPT a Good Teacher Coach? Measuring Zero-Shot Performance For Scoring and Providing Actionable Insights on Classroom Instruction., and . BEA@ACL, page 626-667. Association for Computational Linguistics, (2023)SIGHT: A Large Annotated Dataset on Student Insights Gathered from Higher Education Transcripts., , , and . BEA@ACL, page 315-351. Association for Computational Linguistics, (2023)