Link to preprint: https://arxiv.org/abs/2205.11558
Description of files:
Data
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data/500_gsp_samples_text_human_encoded.npy: Human language embeddings
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data/500_gsp_samples_text_synth_encoded.npy: Synthetic language embeddings
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data/500_gsp_samples_text_synth.npy: Synthetic language descriptions
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data/500_gsp_samples_text_human.npy: Human language descriptions
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data/gsp_samples-recognition_activations-structurePenalty2.npz: Program embeddings
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data/500_gsp_samples.npy: Training boards
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data/gsp_4x4_full.npy: Boards from the GSP chain
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data/gsp_4x4_full_probs.npy: Frequencies of each board in the GSP chain.
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data/data_grulrep.csv: Raw chain data for GSP experiment [network_id: indexes the different GSP chains, active_index: indicates which cell is being changed, degree: indicates which iteration in the chain you’re looking at (0 initial random seed), definition: grid being changed]
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data/gsp_4x4_sample.npy: Test set GSP boards
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data/gsp_4x4_sample_starts.npy: Start tiles for test set GSP boards
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data/gsp_4x4_null_sample.npy: Test set control boards
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data/gsp_4x4_null_sample-starts.npy: Start tiles for test set control boards
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data/hyperparams_grounding.pkl: Hyperparams for grounding agents.
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data/hyperparams_nogrounding.pkl: Hyperparams for non-grounding agents.
Meta-RL Agent Code
- auxillary_model.py: Training code for agents w/ auxillary loss.
- auxillary_polcy.py: Setup for agent training code w/ auxillary loss.
- small_env_lang_4x4.py: Modified training enviornment for grounded meta-rl agent for the GSP task distribution.
- small_env_4x4.py: Training enviornment for baseline meta-rl agent for the GSP task distribution.
- task_performance_zscore.py: Code to calculate task performance metric of paper.
Program Induction with DreamCoder
- ec-master/: Folder with program induction code. This is a fork from: https://github.com/ellisk42/ec The vast majority of the code here is from the public repository of DreamCoder (Ellis et al. 2021) here: https://github.com/ellisk42/ec. Our additions are the implementation of DreamCoder in our enviornment (mostly in: dreamcoder/domains/grid, which has its own readme).