Modern port of Melanie Mitchell's and Douglas Hofstadter's Copycat
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README.md

co.py.cat

GUI

An implementation of Douglas Hofstadter's Copycat algorithm. The Copycat algorithm is explained on Wikipedia, and that page has many links for deeper reading. See also Farglexandria.

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".

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.