Metadata-Version: 1.1
Name: aima
Version: 2015.4.5
Summary: aima -- Artificial Intelligence, A Modern Approach, by Stuart Russell and Peter Norvig
Home-page: https://github.com/hobson/aima
Author: Peter Norvig <peter.norvig@gmail.com>, Darius Bacon <withal@gmail.com>, Spotted Metal? <spottedMetal@gmail.com>, S R Burnet? <srburnet@gmail.com>, Phil Ruggera, Peng Shao, Amit Patil, Ted Nienstedt, Jim Martin, Ben Catanzariti, Hobson Lane <admin@totalgood.com>
Author-email: peter.norvig@gmail.com
License: UNKNOWN
Download-URL: https://github.com/hobson/aima/tarball/2015.4.5
Description: Introduction
        ============
        
        This file gives an overview of the Python code for the algorithms in the
        textbook Artificial Intelligence: A Modern Approach, also known as AIMA.
        The code is offered free for your use under the MIT License. As you may
        know, the textbook presents algorithms in pseudo-code format; as a
        supplement we provide this code. The intent is to implement all the
        algorithms in the book, but we are not done yet.
        
        Prerequisites
        =============
        
        The code is meant for Python 2.5 through 2.7.
        
        How to Browse the Code
        ======================
        
        You can get some use out of the code here just by browsing, starting at
        the root of the source tree or by clicking on the links in the index on
        the project home page. The source code is in the .py files; the .txt
        files give examples of how to use the code.
        
        How to Install the Code
        =======================
        
        If you like what you see, install the code using either one of these
        methods:
        
        From a command shell on your computer, execute the svn checkout command
        given on the source tab of the project. This assumes you have previously
        installed the version control system Subversion (svn). Download and
        unzip the zip file listed as a "Featured download"on the right hand side
        of the project home page. This is currently (Oct 2011) long out of date;
        we mean to make a new .zip when the svn checkout settles down.
        
        You'll also need to install the data files from the aima-data project.
        These are text files that are used by the tests in the aima-python
        project, and may be useful for yout own work.
        
        You can put the code anywhere you want on your computer, but it should
        be in one directory (you might call it aima but you are free to use
        whatever name you want) with aima-python as a subdirectory that contains
        all the files from this project, and data as a parallel subdirectory
        that contains all the files from the aima-data project.
        
        How to Test the Code
        ====================
        
        First, you need to install Python (version 2.5 through 2.7; parts of the
        code may work in other versions, but don't expect it to). Python comes
        preinstalled on most versions of Linux and Mac OS. Versions are also
        available for Windows, Solaris, and other operating systems. If your
        system does not have Python installed, you can download and install it
        for free.
        
        In the aima-python directory, execute the command
        
        ::
        
            python doctests.py -v *.py
        
        The "-v" is optional; it means "verbose". Various output is printed, but
        if all goes well there should be no instances of the word "Failure", nor
        of a long line of "". If you do use the "-v" option, the last line
        printed should be "Test passed."
        
        How to Run the Code
        ===================
        
        You're on your own -- experiment! Create a new python file, import the
        modules you need, and call the functions you want.
        
        Acknowledgements
        ================
        
        Many thanks for the bug reports, corrected code, and other support from
        Phil Ruggera, Peng Shao, Amit Patil, Ted Nienstedt, Jim Martin, Ben
        Catanzariti, and others.
        
Keywords: ai,ml,artificial intelligence,machine intelligence,norvig,russell,agent,bot,book,textbook,algorithm,machine-learning,search
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.5
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Scientific/Engineering :: Mathematics
