Concepts and Causality Lab

Code and data from papers

Code and data from published work are available next to the relevant publications.

More computational cognitive science / causality research at Edinburgh

Bramley lab

Lucas lab

Dan Lassiter

Cognition Computation and Development lab

Zhao lab

R code for counterfactual models of causal judgment

This Github repository contains R scripts for computing predictions for two computational models of causal judgment (the Necessity-Sufficiency and Counterfactual Effect Size models). Note: this is ongoing work.

Agent-based models

These agent-based models of social evolution were developed as a pedagogical tool for the class Psy155: Evolution & Cognition at UCSB. The models are written in python; you can access the Jupyter Notebooks at the following GitHub repository, and also run them online with binder. Models include:

hawk/dove

kin selection

kin recognition

group selection