iandanforth

There is almost always a goal

A goal needs to be able to *start* or *modify* behavior.

The spatial representation is a concatenation of senses and intended movement

At some level that combination needs to be represented uniquely. Aka few enough possibilities to represent them all.

When a goal is achieved the behavior that led to it needs to be reinforced.

iandanforth

import subprocess

def getMacModel():
  '''
  Returns the Model Identifier for the current machine.
  '''
  
  cmd = "sysctl -n hw.model"
  cmdOut = subprocess.check_output(cmd, shell=True)
  

iandanforth

#!/usr/bin/env python

import os
import dynamixel
import time
import sys
import subprocess
import optparse
import yaml

iandanforth

#-------------------------------------------------------------------------------
# Copyright (C) 2013 Numenta Inc. All rights reserved.
#
# The information and source code contained herein is the
# exclusive property of Numenta Inc.  No part of this software
# may be used, reproduced, stored or distributed in any form,
# without explicit written authorization from Numenta Inc.
#-------------------------------------------------------------------------------
desc = """
This tool will find instances with the tag specified in the accompanying

iandanforth

  

  ########
  ### Assuming Tag Key == 'params' and Tag Value = 'frontend:foo:bar:numenta'
  tag = 'params'
  filters = {}
  if tag:
    filters["tag-key"] = tag
  
  # Stupid EC2 wrapper needs to be removed  

iandanforth

#! /usr/bin/python

import optparse

def main(options):
    '''
    Performs the amazingly useful tasks for this command line tool
    '''
    pass

iandanforth

#! /usr/bin/python

import os
import subprocess
import time

iteration = 1

def main():

iandanforth

#############################################################################
# Full Imports

from __future__ import division
import math
import random

"""
This is a pure Python implementation of the K-means Clustering algorithmn. The
original can be found here:

iandanforth

'''
How to work with the AX1 Sensor

git clone git@github.com:iandanforth/pydynamixel.git
git checkout axs1
python setup.py install
'''

import dynamixel
import time

iandanforth

#!/usr/bin/python
import time
from random import randint

"""
#############################
Learning Loop

Our scenario is that of a simple creature in a very simple world.