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Rush Hour

Code to reproduce figures from paper.

Installation

Instructions for how to install the necessary files

Usage (Experiment)

Instructions for how to run experiments

Usage (Analysis)

Instructions for how to run analysis

Demo(s)

Description of demos

Authors and Acknowledgements

Jeroen Olieslagers

License

The code is released under the terms of the MIT License.

rush_hour
├── README.md
├── Project.toml                : tells julia which packages to install
├── Manifest.toml
├── demos
├── figures                     : contains all figures from paper
├── data
│   ├── processed_data
│   │   ├── binned_stats.csv
│   │   ├── d_goals_prbs.jld3
│   │   ├── df_models.csv
│   │   ├── df_stats.csv
│   │   ├── dict.jld2
│   │   ├── fitted_params.jld2
│   │   ├── mc_dict.jld2
│   │   ├── params.jld2
│   │   ├── stuff.jld2
│   │   └── true_params.jld2
│   └── raw_data
│       ├── problems            : directory containing all puzzles for all move data from experiment in .json format
│       └── all_subjects.csv    : raw data
└── src
    ├── and_or_model.jl         : AND-OR tree traversal model
    ├── and_or_trees.jl         : generate AND-OR trees
    ├── data_analysis.jl        : additional functions to analyze data for supplementary figures
    ├── load_scripts.jl         : load all functions, scripts, and data
    ├── main.jl                 : central script
    ├── markov_chains.jl        : additional functions for forwar search model
    ├── mixed_effects_models.jl : additional functions for forwar search model
    ├── model_fitting.jl        : function to fit and cross-validated models
    ├── models.jl               : all models to be tested
    ├── plotting.jl             : functions to produce figures from paper
    ├── pre_process.jl          : filter and process data into suitable format
    ├── representation.jl       : types, structs, and converter functions
    ├── rush_hour.jl            : game logic
    ├── RushHour.jl             : to do with the environment, not important
    ├── search.jl               : BFS to compute d_goal for every state
    ├── standard_errors.jl      : run simulations to confirm within-participant standard error
    ├── summary_statistics.jl   : compute summary statistics for every state
    └── visualization.jl        : board state and AND-OR tree visualizers

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