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Supplementary Information: Infinite Ends from Finite Samples: Open-Ended Goal Inference as Top-Down Bayesian Filtering of Bottom-Up Proposals
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Description: Supplementary information for Zhi-Xuan, T., Kang, G., Mansinghka, V., & Tenenbaum, J. B. (2024). Infinite Ends from Finite Samples: Open-Ended Goal Inference as Top-Down Bayesian Filtering of Bottom-Up Proposals. Proceedings of the 46th Annual Meeting of the Cognitive Science Society.
Source code for this paper can be found at https://github.com/ztangent/OpenEndedBlockWords.jl.
The dataset folder contains all animation stimuli, along with the PDDL problems, plans, and domain file used to generate them.
The results folder contains:
- The human data we collected (
human_results.zip). - Aggregated model outputs (
model_results.zip). - Results from individual model runs (
individual_model_…
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