An implementation of Douglas Hofstadter and Melanie Mitchell's Copycat algorithm. The Copycat algorithm is explained on Wikipedia, in Melanie Mitchell's Book Analogy-making as perception, and in this paper. The wikipedia page has additional links for deeper reading. See also FARGonautica, where a collection of Fluid Concepts projects are available.

This implementation is a copycat of Scott Boland's Java implementation. The original Java-to-Python translation work was done by J Alan Brogan (@jalanb on GitHub). The Java version has a GUI similar to the original Lisp; this Python version has no GUI code built in but can be incorporated into a larger GUI program.

J. Alan Brogan writes:

In cases where I could not grok the Java implementation easily, I took ideas from the LISP implementation, or directly from Melanie Mitchell's book "Analogy-Making as Perception".

Running the command-line program

To clone the repo locally, run these commands:

$ git clone https://github.com/fargonauts/copycat.git
$ cd copycat/copycat
$ python main.py abc abd ppqqrr --iterations 10

The script takes three or four arguments. The first two are a pair of strings with some change, for example "abc" and "abd". The third is a string which the script should try to change analogously. The fourth (which defaults to "1") is a number of iterations.

This might produce output such as

ppqqss: 6 (avg time 869.0, avg temp 23.4)
ppqqrs: 4 (avg time 439.0, avg temp 37.3)

The first number indicates how many times Copycat chose that string as its answer; higher means "more obvious". The last number indicates the average final temperature of the workspace; lower means "more elegant".

Code structure

This Copycat system consists of 4,981 lines of Python code across 40 files. Here's a breakdown.

Core Components:

codeletMethods.py: 1,124 lines (largest file)
curses_reporter.py: 436 lines
coderack.py: 310 lines
slipnet.py: 248 lines

Workspace Components:

group.py: 237 lines
bond.py: 211 lines
correspondence.py: 204 lines
workspace.py: 195 lines
workspaceObject.py: 194 lines

Control Components:

temperature.py: 175 lines
conceptMapping.py: 153 lines
rule.py: 149 lines
copycat.py: 144 lines

GUI Components:

gui/gui.py: 96 lines
gui/workspacecanvas.py: 70 lines
gui/status.py: 66 lines
gui/control.py: 59 lines

The system is well-organized with clear separation of concerns:

Core logic (codelets, coderack, slipnet)
Workspace management (groups, bonds, correspondences)
Control systems (temperature, rules)
User interface (GUI components)

The largest file, codeletMethods.py, contains all the codelet behavior implementations, which makes sense as it's the heart of the system's analogical reasoning capabilities.

{code.py}README.md Files

We've got an LLM to document every code file, so people can look at a particular readme before delving into the work (Here's one Example.

Installing the module

To install the Python module and get started with it, run these commands:

$ pip install -e git+git://github.com/fargonauts/copycat.git#egg=copycat
$ python
>>> from copycat import Copycat
>>> Copycat().run('abc', 'abd', 'ppqqrr', 10)
{'ppqqrs': {'count': 4, 'avgtime': 439, 'avgtemp': 37.3}, 'ppqqss': {'count': 6, 'avgtime': 869, 'avgtemp': 23.4}}

The result of run is a dict containing the same information as was printed by main.py above.