105 lines
4.7 KiB
Markdown
105 lines
4.7 KiB
Markdown
Copycat
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=========
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An implementation of [Douglas Hofstadter](http://prelectur.stanford.edu/lecturers/hofstadter/) and [Melanie Mitchell](https://melaniemitchell.me/)'s Copycat algorithm.
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The Copycat algorithm is explained [on Wikipedia](https://en.wikipedia.org/wiki/Copycat_%28software%29), in Melanie Mitchell's Book [Analogy-making as perception](https://www.amazon.com/Analogy-Making-Perception-Computer-Modeling-Connectionism/dp/026251544X/ref=sr_1_5?crid=1FC76DCS33513&dib=eyJ2IjoiMSJ9.TQVbRbFf696j7ZYj_sb4tIM3ZbFbuCIdtdYCy-Mq3EmJI6xbG5hhVXuyOPjeb7E4b8jhKiJlfr6NnD_O09rEEkNMwD_1zFxkLT9OkF81RSFL4kMCLOT7K-7KnPwBFbrc9tZuhLKFOWbxMGNL75koMcetQl2Lf6V7xsNYLYLCHBlXMCrusJ88Kv3Y8jiPKwrEr1hUwhWB8vtwEG9vSYXU7Gw-b4fZRNNbUtBBWNwiK3k.IJZZ8kA_QirWQK1ax5i42zD2nV7XvKoPYRgN94en4Dc&dib_tag=se&keywords=melanie+mitchell&qid=1745436638&sprefix=melanie+mitchell%2Caps%2C206&sr=8-5#), and in [this paper](https://github.com/Alex-Linhares/FARGonautica/blob/master/Literature/Foundations-Chalmers.French.and.Hofstadter-1992-Journal%20of%20Experimental%20and%20Theoretical%20Artificial%20Intelligence.pdf). The wikipedia page has additional links for deeper reading. See also [FARGonautica](https://github.com/Alex-Linhares/Fargonautica), where a collection of Fluid Concepts projects are available.
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This implementation is a copycat of Scott Boland's [Java implementation](https://archive.org/details/JavaCopycat).
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The original Java-to-Python translation work was done by J Alan Brogan (@jalanb on GitHub).
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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.
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J. Alan Brogan writes:
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> In cases where I could not grok the Java implementation easily, I took ideas from the
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> [LISP implementation](http://web.cecs.pdx.edu/~mm/how-to-get-copycat.html), or directly
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> from [Melanie Mitchell](https://en.wikipedia.org/wiki/Melanie_Mitchell)'s book
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> "[Analogy-Making as Perception](http://www.amazon.com/Analogy-Making-Perception-Computer-Melanie-Mitchell/dp/0262132893/ref=tmm_hrd_title_0?ie=UTF8&qid=1351269085&sr=1-3)".
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Running the command-line program
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--------------------------------
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To clone the repo locally, run these commands:
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```
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$ git clone https://github.com/fargonauts/copycat.git
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$ cd copycat/copycat
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$ python main.py abc abd ppqqrr --iterations 10
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```
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The script takes three or four arguments.
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The first two are a pair of strings with some change, for example "abc" and "abd".
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The third is a string which the script should try to change analogously.
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The fourth (which defaults to "1") is a number of iterations.
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This might produce output such as
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```
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ppqqss: 6 (avg time 869.0, avg temp 23.4)
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ppqqrs: 4 (avg time 439.0, avg temp 37.3)
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```
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The first number indicates how many times Copycat chose that string as its answer; higher means "more obvious".
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The last number indicates the average final temperature of the workspace; lower means "more elegant".
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Code structure
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---------------------
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This Copycat system consists of 4,981 lines of Python code across 40 files. Here's a breakdown.
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Core Components:
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- codeletMethods.py: 1,124 lines (largest file)
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- curses_reporter.py: 436 lines
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- coderack.py: 310 lines
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- slipnet.py: 248 lines
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Workspace Components:
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- group.py: 237 lines
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- bond.py: 211 lines
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- correspondence.py: 204 lines
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- workspace.py: 195 lines
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- workspaceObject.py: 194 lines
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Control Components:
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- temperature.py: 175 lines
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- conceptMapping.py: 153 lines
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- rule.py: 149 lines
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- copycat.py: 144 lines
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GUI Components:
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- gui/gui.py: 96 lines
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- gui/workspacecanvas.py: 70 lines
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- gui/status.py: 66 lines
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- gui/control.py: 59 lines
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The system is well-organized with clear separation of concerns:
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- Core logic (codelets, coderack, slipnet)
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- Workspace management (groups, bonds, correspondences)
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- Control systems (temperature, rules)
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- User interface (GUI components)
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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.
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{code.py}README.md Files
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---------------------
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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](main_README.md)).
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Installing the module
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---------------------
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To install the Python module and get started with it, run these commands:
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```
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$ pip install -e git+git://github.com/fargonauts/copycat.git#egg=copycat
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$ python
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>>> from copycat import Copycat
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>>> Copycat().run('abc', 'abd', 'ppqqrr', 10)
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{'ppqqrs': {'count': 4, 'avgtime': 439, 'avgtemp': 37.3}, 'ppqqss': {'count': 6, 'avgtime': 869, 'avgtemp': 23.4}}
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```
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The result of `run` is a dict containing the same information as was printed by `main.py` above.
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