This project reproduces Langley’s BACON system for Computational Scientific Discovery. It uses his book as the main inspiration to reimagine his methods using Python.
This project recreates BACON.1, BACON.3, BACON.5 and BACON.6. It also has functionality for novel methodologies, including my own creations and a Monte-Carlo Tree Search to traverse the space.
The datasets tested on were synthetic and can be found in datasets.py.
In main.py the full list of methods used in the Space of Data and Space of Laws are shown and can be customised by the user in an args file. For example, to run on the Ideal Gas Law with 3% noise in the dependent variable, the command is:
python3 main.py --dataset ideal --noise 0.03 --args args/ideal/ideal30.json
With the args file user customisable.
This project was completed as a dissertation for the Part III Computer Science course at the University of Cambridge. The final report is in the dissertation.pdf.