Introduction to AI

Article by www.csedukit.com

Topic:Artificial Intelligence(AI) and Some typical problems in AI 

Artificial Intelligence is concerned with the design of intelligence in an artificial device.
The term was coined by McCarthy in 1956

So related to the definition we have two entities 

1. Intelligence
2. artificial device

where intelligence characterize humans and artificial device is any artificial artifacts

By considering the intelligence we have another two options 

– A system with intelligence is expected to behave as intelligently as a human
– A system with intelligence is expected to behave in the best possible manner 

Now we have the point behavior ,it also considered to be two parts.
– Are we looking at the thought process or reasoning ability of the system?
– Or are we only interested in the final manifestations of the system in terms of its actions?

Given this scenario different interpretations have been used by different researchers as defining the scope and view of Artificial Intelligence.

1. One view is that artificial intelligence is about designing systems that are as intelligent as humans.
This view involves trying to understand human thought and an effort to build machines that emulate the human thought process. This view is the cognitive science approach to AI.

2. The second approach is best embodied by the concept of the Turing Test. Turing held that in future computers can be programmed to acquire abilities rivaling human intelligence. As part of his argument Turing put forward the idea of an 'imitation game', in which a human being and a computer would be interrogated under conditions where the interrogator would not know which was which, the communication being entirely by textual messages. Turing argued that if the interrogator could not distinguish them by questioning, then it would be unreasonable not to call the computer intelligent. Turing's 'imitation game' is now usually called 'the Turing test' for intelligence.

3. Logic and laws of thought deals with studies of ideal or rational thought process and inference. The emphasis in this case is on the inferencing mechanism, and its properties. That is how the system arrives at a conclusion, or the reasoning behind its selection of actions is very important in this point of view. The soundness and completeness of the inference mechanisms are important here.

4. The fourth view of AI is that it is the study of rational agents. This view deals with building machines that act rationally. The focus is on how the system acts and performs, and not so much on the reasoning process. A rational agent is one that acts rationally, that is, is in the best possible manner.

Typical AI problems

While studying the typical range of tasks that we might expect an “intelligent entity” to perform, we need to consider both “common-place” tasks as well as expert tasks.
Examples of common-place tasks include

– Recognizing people, objects.
– Communicating (through natural language).
– Navigating around obstacles on the streets

These tasks are done matter of factly and routinely by people and some other animals.

Expert tasks include:
• Medical diagnosis.
• Mathematical problem solving
• Playing games like chess
These tasks cannot be done by all people, and can only be performed by skilled specialists.