https://github.com/murraylab/instrumentallatentstatelearning
Code associated with the publication on latent state learning
https://github.com/murraylab/instrumentallatentstatelearning
Last synced: 4 months ago
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Code associated with the publication on latent state learning
- Host: GitHub
- URL: https://github.com/murraylab/instrumentallatentstatelearning
- Owner: murraylab
- Created: 2022-07-18T19:15:19.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2023-03-09T13:39:46.000Z (over 3 years ago)
- Last Synced: 2024-12-31T06:14:57.295Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 27.1 MB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# MultiLatentStateInstrumentalLearning
Copyright 2021, Warren Woodrich Pettine
This code contains simulations and data analysis used in "Pettine, W. W., Raman, D. V., Redish, A. D., Murray, J. D.
“Human generalization of internal representations through prototype learning with goal-directed attention,” March 2023, Nature Human Behavior.
https://www.nature.com/articles/s41562-023-01543-7
For examples of running the code base, see the examples.py file in the main directory.
# Installation
All code was written using python version 3.7. Please see the requirements file for required packages. To install the
requirements, just run.
```bash
pip install -r requirements.txt
```
# Organization
The code is organized in the following packages.
- simulations
- subjects
- utils
- analysis
- plots
See package modules for details on each function.
In addition, the main directory contains the module 'examples.py' that runs the algorithmic model on relevant experiments.
## simulations
The simulations package contains all code necessary to simulate the various models. It is organized in the following
modules:
- algorithmicmodels
- neuralnetwork
- parameters
- experiments
### algorithmicmodels.py
This module contains the main code for the prototype and exemplar algorithmic models.
### neuralnetwork.py
This module contains the code to run the neural network simulations. This module is unfinished.
### parameters.py
Module for creating parameters dictionaries to create agents, networks and the worlds with with they interact.
### experiments.py
Module that creates specific experiments used in the paper.
## utils
This package contains the module utils.py, which organizes Various useful functions, such as those for unit testing.
## analysis
This package contains Code for higher-level analyses of behavior and model fun
- general
- plotfunctions
### general.py
Functions used for general analysis
### plotfunctions.py
Functions used to plot the data