Youtube video and relevant image offering a method by which to extract information from a greyscale image with an example of a linear filter (equation).

 

Extracting Features from a Greyscale image

Linear Filter

The purpose of this post is to document my research in the comprehension of artificial intelligence and the simulation/creation of an artificial life form.

Artificial Intelligence – Research Question and Hypothesis

Topic: Artificial Intelligence

Narrowed Topic: Artificially intelligent algorithms and artificial life.

Issue: Advancing and improving artificial intelligence for the purpose of creating artificial life forms, and/or artificial life simulations.

Research Questions: Of the existing types of artificially intelligent algorithms, which has the greatest potential to improve and/or expand our current capabilities in the use ...

Bring computational knowledge to your web, mobile, desktop, and enterprise applications

http://products.wolframalpha.com/api/

Provided by Know Labs in Partnership with Stanford University’s Engineering Department
URL: http://www.ai-class.com/

“Online Introduction to Artificial Intelligence is based on Stanford CS221, Introduction to Artificial Intelligence. This class introduces students to the basics of Artificial Intelligence, which includes machine learning, probabilistic reasoning, robotics, and natural language processing.”
Source – ai-class.com

Problem Solving

Definition of a problem:

• Initial State
• Action (state) –> { action1, action2, action3 … }
  Takes a state as input, and returns a set of possible actions.
• Result (state, action) ...
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Provided by Know Labs in Partnership with Stanford University’s Engineering Department
URL: http://www.ai-class.com/

“Online Introduction to Artificial Intelligence is based on Stanford CS221, Introduction to Artificial Intelligence. This class introduces students to the basics of Artificial Intelligence, which includes machine learning, probabilistic reasoning, robotics, and natural language processing.

The objective of this class is to teach you modern AI. You learn about the basic techniques and tricks of the trade, at the same level we teach our Stanford students. We also ...

This article is focused on how it is possible that an algorithm can read 1 bit of data yet store the results of 3 bits.

The concept behind this idea is quite simple. We know that bits are sent via an encoded signal from the CPU of an informaton system. It is also known, that at the base of all CPU’s, the machine language is based on binary bits, represented as values of 1 or 0.

Here is an example of how the bit string ...

Problem solving techniques can be applied to both life and the field of computer science. In both instances, there are different methodologies that can be applied; for, the use of a specific methodology is directly dependent on the type of problem that must be solved.

This article will define the different types pf problem solving methodologies, as well as the different types of problems they can solve.

Request-Response-Result Methodology

The request-response-result methodology works best ...

Video Samples of Artificial Intelligence as Applied to Robotics

Mars Rover – Curiosity

Azimo

Artificial Intelligence – Ginectic Programming

The purpose of this post is to offer a comprehensive listing of resources related to the ginetic algorithm, which is being further developed by John Koza of Standford University.

John Holland – Ginetic Algorithms (1975)

Genetic Programming Inc.
A privately funded research group that does research in applying genetic programming.

What is Ginetic Programming?

Springer: Ginetic Programming Publications

ECJ 20
A Java-based Evolutionary Computation Research System

Yahoo Genetic Programming Group/Mailing List

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Neural Network Defined

A neural network is an information system that is modeled after the human brain and nervous system. The network consists of a large number of units that are separated into 3 separate types (1) input units, (2) output units, and (3) hidden units. These units model the 3 units of the human nervous system (1) sensory neurons (input), (2) motor neurons (output), and (3) all ...