Metadata-Version: 1.0
Name: AIKIF
Version: 0.0.1
Summary: Artificial Intelligence Knowledge Information Framework
Home-page: http://pypi.python.org/pypi/aikif/
Author: Duncan Murray
Author-email: djmurray@acutesoftware.com.au
License: LICENSE.txt
Description: #AIKIF
        #####Artificial Intelligence Knowledge Information Framework
        *NOTE - this is very much an experimental work in progress* - the code runs, but wont do anything useful at this stage
        
        ##Overview
        This is an example framework to capture the flow of information initially for personal data management, but ultimately useful for AI applications.<br />
        Initially it will be populated and tested for human use, but includes tests and verification process for future ‘General AI’s.<br />
        Functions (Octave, Python, SQL) are called at set stages of the AI process which log the results into a standard database schema.<br /><br />
        
        
        ###Quick Start
        The goal is to get any set of information and parse it into a consistent format so a machine can read it.<br />
        For example:<br />
        	Project Management<br/>
            Code Management<br/>
            Personal Information Management<br/>
        
        ##Programs
        ###Main Programs
        AI.py			- sample main program to show a trivial example of logging data<br />
        view.py			- simple command driven procedure to show various details of the system<br />
        index.py		- creates text indexes of all the files<br />
        search.py		- searches, using both indexes and ontologies<br />
        go_web_aikif.bat- starts the web server for the AIKIF admin interface
        
        ###Toolbox
        Various modules which contain generic functions
        
        ###DataTools
        collection of modules to manage data transformations
        
        ###Standard Library Programs
        AIKIF_utils.py	- standard utils for the filelists<br />
        fileMapping.py	- main routine that decides what the output files will be called<br />
        security.py		- manages security, which will allow users to have private data (not the norm for this)<br />
        
        ###Data Load programs
        These programs are used to load a specific dataset, the code used to parse each file is in a separate load procedure<br />
        processRawData.py			- this calls all data load programs and logs results<br />
        create_word_lists.py		- loads a list of nouns, verbs, adjectives from web into local structures<br />
        loadCountry_Gdeltproject.py	- loads a country reference file<br />
        loadPIM_Filelist.py			- loads a list of local files into objects, events, photos<br />
        loadPIM_shopping.py			- sample to show how a personal shopping list is loaded<br />
        
        ###Experimental programs - probably wont be used
        addRawData.py	- using word lists, this experiments with parsing information as a bag of words<br />
        AIKIF_create.py	- creates default set of filelists and data files (DONT run this if you start using the software)<br />
        
        
        ##Data                  
        Raw Data        - raw information from any source<br />
        BIAS tables     - weightings to rank data based on various criteria (source, person, format)<br />
        Weighted Data   - data ranked according to weightings / human verification results<br />
        Algorithms      - database of algorithms, split into componants <br />
        Concepts        - generic concepts about information<br />
        Concepts_Data   - links to concepts and data<br />
        New_Concepts    - randomly generated possible concept links based on ratings<br />
        
        ##Tracking generic AI concepts / Logging
        ###Goal Management
        goal_types      - 0=supergoal:{'Be Friendly to humans'}, 1=endgoals ['assist', 'solve', 'learn'], 2=goals [], 3=subgoals []<br />
        goals           - list of goals to achieve<br />
        preferences     - ranked order of topics to focus on<br />
        
        ###Decision Making
        commands        - requested commands from human operator<br />
        action          - list of actions (AI plans) <br />
        outcomes        - list of possible outcomes with impacts, liklihood, past stats, ratings<br />
        
        ###Source Data
        -----------
        rawData         - raw text feed of data from datasets, web, social media<br />
        websites        - reference file on websites with biases<br />
        people          - reference file on people / usernames with biases<br />
        
        ###Data Processing Tables
        ----------------------
        bias            - details on bias's for a given source of rawData<br />
        feedback        - human reasoning behind various BIAS weightings and human votes (+/-) on rawData<br />
        facts          - result of processed rawData taking into account sources, biases and feedback<br />
        knowledge      - understanding of facts *(no idea how this will be implemented)<br />
        
        
        
        
        
Platform: UNKNOWN
