The Computer Revolution/Artificial Intelligence/Branches of & Applying AI

AI – Intelligence, Intelligence Agents & Key Areas of AI Research
Humans throughout history appear to have attempted to recreate themselves in some form of artificial person. In fact, the earliest examples may be heralded from the Greek Gods and the “intellectual roots of AI, and the concept of intelligent machines, may be found in Greek mythology” (http://www.aaai.org/AITopics/html/history.html  Retrieved Dec 7, 2006). For a more comprehensive look at, but still brief history of AI, one can consult a chronology of significant events by Bruce G. Buchanan (http://www.aaai.org/AITopics/bbhist.html  Retrieved Dec 7, 2006).

AI or Artificial Intelligence is a huge field of study with many subfields, but the main “underlying theme is the idea of an intelligent agents …” which are considered to be “systems that can decide what to do and then do it” (http://aima.cs.berkeley.edu/preface.html  Retrieved Dec 7, 2006). Intelligent agents are “… a form of software with built-in intelligence that monitors work patterns, asks questions, and performs work tasks on your behalf” (Williams & Sawyer, 2007, Using Information Technology: A Practical Introduction to Computers & Communications,  Montreal: McGraw-Hill Irwin, p. 442). Therefore, it is not uncommon to encounter references in AI literature about aspects of trying to achieve “intelligence” or making machines “intelligent,” especially in the computer world where attempts are made to make intelligent computer programs or to use computers to understand human intelligence. So, “intelligence is the computational part of the ability to achieve goals in the world, [but there exists] varying kinds and degrees of intelligence [that] occur in people, many animals and some machines,” so the whole idea of AI is extremely complex – as are humans themselves (http://www-formal.stanford.edu/jmc/whatisai/whatisai.html  Retrieved 7, 2006).

But it is generally considered a possibility that human intelligence is attainable, especially after the advent of modern computers following World War II which made it “… possible to create programs that perform difficult intelligent tasks … “ and in combination with “general purpose methods and tools … [which] allow similar tasks to be performed” (http://www.aaai.org/AITopics/html/history.html  Retrieved Dec 7, 2006). In fact, for many of us, we are oblivious to how much AI is already a big part of our everyday life. Some of applications already in existence can be found at http://www.aaai.org/AITopics/html/applications.html (Retrieved Dec 7, 2006). The next time that annoying little Microsoft Office Assistant gets in your face, believe that AI is at work for you.

There are many areas involved in AI research, but some key ones to note are: knowledge acquisition and knowledge base development, knowledge representation and reasoning, machine learning or computational approach to learning, robotics or application of artificial intelligence techniques, and computer vision based on sensed images (http://www.ai.cse.unsw.edu.au/  Retrieved Dec 7, 2006). Likewise, there are different research areas. Two main and interconnected lines of research include one that is “biological” in nature and the other that is “phenomenal.” The former stems from the basic premise that humans are intelligent so AI should be involved in the “… study of humans and attempt to imitate their psychology and physiology,” while the latter is primarily focused on the world and the view that research needs to be “… based on studying and formalizing common sense facts about the world and the problems [it] … presents to the achievement of goals”  (http://www-formal.stanford.edu/jmc/whatisai/node4.html  Retrieved Dec 7, 2006).

No doubt there is a need for both streams and a great deal of collaboration between them. We can revisit the definition of AI see that, in fact, “… artificial intelligence (AI) [is] are group of related technologies used for developing machines to emulate human qualities …” (Williams & Sawyer, p. 440).

Epistemology
Epistemology is the study of knowledge. This study tries to figure out how computers and humans determine what is accurate (true) knowledge and what is inaccurate (false) knowledge. Obviously it is much easier for humans to comprehend what is true or false from background and learned information; however this study aims to question how can a computer determine what is right and wrong. Epistemology, in simple words, concerns itself with the study of the knowledge that can prove useful in the study of the solving of the problems that plague the world. Epistemology, although conventionally considered a branch of philosophy, has managed to carve for itself a niche in artificial engineering. As a branch of artificial intelligence however, epistemology focuses on answering four core questions: What is knowledge? How is knowledge acquired? What do people know? How do we know what we know? The term ‘Epistemology’ was first introduced into the English language by the Scottish philosopher James Frederick Ferrier. It was during his lifetime that the world got to know better the fine and finer nuances of epistemology.

Default Reasoning
This branch of artificial intelligence means that conclusions can be made by given a certain amount of information and fact. People conclude things based on a limited amount of information. This type of reasoning is based on our background knowledge, education, socialization and partly opinion. I sort of feel this type of reasoning is somewhat like “Jumping to Conclusions”?? With any conclusion or statement you make based on default reasoning you always run the risk of being proven wrong if additional information is obtained that changes the way you would conclude the information.

Pattern Recognition
Pattern Recognition is the computers vision not unlike the way your eyes view patterns and recognize objects. It is a computers way of figuring out what an object is by use of a pattern--115.249.219.114 (discuss) 03:32, 6 May 2013 (UTC).