Python code for the book *Artificial Intelligence: A Modern Approach.*

When complete, this project will cover all the major topics in the book, for each topic, such as `logic`, we will have the following [Python 3.5](https://www.python.org/downloads/release/python-350/) files:

- `logic.py`: Implementations of all the pseudocode algorithms in the book.

- `logic_test.py`: A lightweight test suite, using `assert` statements, designed for use with `py.test`.

- `logic.ipynb`: A Jupyter notebook, with examples of usage. Does a `from logic import *` to get the code.

There are a few style rules that are unique to this project:

- The first rule is that the code should correspond directly to the pseudocode in the book. When possible this will be almost one-to-one, just allowing for the syntactic differences between Python and pseudocode, and for different library functions.

- Don't make a function more complicated than the pseudocode in the book, even if the complication would add a nice feature, or give an efficiency gain. Instead, remain faithful to the pseudocode, and if you must, add a new function (not in the book) with the added feature.

- I use functional programming in many cases, but not exclusively; let the book's pseudocode be the guide. In general, pure functions (with no side effects) are prefered, but functions with side effects, and classes, can be used where appropriate.

Beyond the above rules, we default to [Pep 8](https://www.python.org/dev/peps/pep-0008), with a few minor exceptions: