06a42cc746
- Add CLAUDE.md with project guidance for Claude Code - Add LaTeX/ with paper and figure generation scripts - Remove papers/ directory (replaced by LaTeX/) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
90 lines
3.2 KiB
Markdown
90 lines
3.2 KiB
Markdown
# CLAUDE.md
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This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
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## Project Overview
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This is a Python implementation of Douglas Hofstadter and Melanie Mitchell's Copycat algorithm for analogical reasoning. Given a pattern like "abc → abd", it finds analogous transformations for new strings (e.g., "ppqqrr → ppqqss").
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## Python Environment
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Use Anaconda Python:
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```
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C:\Users\alexa\anaconda3\python.exe
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```
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## Common Commands
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### Run the main program
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```bash
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python main.py abc abd ppqqrr --iterations 10
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```
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Arguments: `initial modified target [--iterations N] [--seed N] [--plot]`
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### Run with GUI (requires matplotlib)
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```bash
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python gui.py [--seed N]
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```
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### Run with curses terminal UI
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```bash
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python curses_main.py abc abd xyz [--fps N] [--focus-on-slipnet] [--seed N]
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```
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### Run tests
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```bash
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python tests.py [distributions_file]
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```
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### Install as module
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```bash
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pip install -e .
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```
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Then use programmatically:
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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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```
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## Architecture (FARG Components)
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The system uses the Fluid Analogies Research Group (FARG) architecture with four main components that interact each step:
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### Copycat (`copycat/copycat.py`)
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Central orchestrator that coordinates the main loop. Every 5 codelets, it updates the workspace, slipnet activations, and temperature.
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### Slipnet (`copycat/slipnet.py`)
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A semantic network of concepts (nodes) and relationships (links). Contains:
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- Letter concepts (a-z), numbers (1-5)
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- Structural concepts: positions (leftmost, rightmost), directions (left, right)
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- Bond/group types: predecessor, successor, sameness
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- Activation spreads through the network during reasoning
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### Coderack (`copycat/coderack.py`)
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A probabilistic priority queue of "codelets" (small procedures). Codelets are chosen stochastically based on urgency. All codelet behaviors are implemented in `copycat/codeletMethods.py` (the largest file at ~1100 lines).
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### Workspace (`copycat/workspace.py`)
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The "working memory" containing:
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- Three strings: initial, modified, target (and the answer being constructed)
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- Structures built during reasoning: bonds, groups, correspondences, rules
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### Temperature (`copycat/temperature.py`)
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Controls randomness in decision-making. High temperature = more random exploration; low temperature = more deterministic choices. Temperature decreases as the workspace becomes more organized.
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## Key Workspace Structures
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- **Bond** (`bond.py`): Links between adjacent letters (e.g., successor relationship between 'a' and 'b')
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- **Group** (`group.py`): Collection of letters with a common bond type (e.g., "abc" as a successor group)
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- **Correspondence** (`correspondence.py`): Mapping between objects in different strings
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- **Rule** (`rule.py`): The transformation rule discovered (e.g., "replace rightmost letter with successor")
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## Output
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Results show answer frequencies and quality metrics:
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- **count**: How often Copycat chose that answer (higher = more obvious)
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- **avgtemp**: Average final temperature (lower = more elegant solution)
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- **avgtime**: Average codelets run to reach answer
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Logs written to `output/copycat.log`, answers saved to `output/answers.csv`.
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