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METATOOL_UoS

This codebase provides a minimal model of tool innovation that involves an active inference agent making generalised inferences about the tool structure required to solve an extension‐of‐reach task. For a comprehensive understanding of the methodologies and theories associated with this codebase, please refer to our research paper Collis et al., 2023. The paper provides in‐depth insights and discussions on the concepts, experiments, and findings that form the basis of this project. We encourage readers and users of this repository to consult the paper for a more detailed exposition of the work presented here.

Documentation

For details on the parameters and an explanation of the model, please see accompanying article: D1_2_simple_metacognitive_model

Installation

To get started, you can easily download and run the scripts provided. Everything you need to run the scripts is included in the repository.

Pre-requisites

A Python Integrated Development Environment (IDE) or any Python execution environment is required to run the Python scripts.

1. Clone the Repository

  • Ensure you have git installed.
  • Open your terminal or command prompt.
  • Navigate to the directory where you want to clone the repository.
  • Run the following command: git clone https://github.com/PoppyCollis/METATOOL_UoS.git
  • This command will create a local copy of the repository on your machine.
  • ALTERNATIVELY: you can simply download the repository as a .zip file and extract it to a local directory

2. Navigate to the Repository Directory

cd path/to/directory

4. Install Dependencies

  • NumPy
  • SciPy
  • Pandas
  • Matplotlib
  • Seaborn

4. Run the Scripts

Once all dependencies are installed, you can run the scripts as instructed in the specific script documentation D1_2_simple_metacognitive_model. Main scripts:

  • tool_state_model.py
  • affordance_model.py

Authors: P. F. Kinghorn and P. Collis