Understanding in Artificial Intelligence

UNDERSTANDING

Understanding is the simplest procedure of all human beings. Understanding means ability to determine some new knowledge from a given knowledge. For each action of a problem, the mapping of some new actions is very necessary. Mapping the knowledge means transferring the knowledge from one representation to another representation. For example, if you will say “I need to go to New Delhi” for which you will book the tickets. The system will have “understood” if it finds the first available pla ne to New Delhi. But if you will say the same thing to you friends, who knows that your family lives in “New Delhi”, he/she will have “understood” if he/she rea lizes that there may be a problem or occasion in your family. For people, understanding applies to inputs from all the senses. Computer understanding has so far been applied primarily to images, speech and typed languages. It is important to keep in mind that the success or failure of an “understanding” problem ca n rarely be measured in an absolute sense but must instead be measured with respect to a particular task to be performed. There are some factors that contribute to the difficulty of an understanding problem.

(a)  If the target representation is very complex for which you cannot map from the original representation.

(b) There are different types of mapping factors may arise like one-to-one, one-to-many and many-to-many.

(c)  Some noise or disturbing factors are also there.

(d) The level of interaction of the source components may be complex one.

(e)  The problem solver might be unknown about some more complex problems.

(f)   The intermediary actions may also be unavailable.

Consider an example of an English sentence which is being used for communication with a keyword-based data retrieval system. Suppose I want to know all about the temples in India. So I would need to be translated into a representation such as The above sentence is a simple sentence for which the corresponding representation may be easy to implement. But what for the complex queries?

Consider the following query.

“Ram told Sita he would not eat apple with her. He has to go to the office”. This type of complex queries can be modeled with the conceptual dependency representation which is more complex than that of simple representation. Constructing these queries is very difficult since more informationare to be extracted. Extracting more information will require some more knowledge.

Also the type of mapping process is not quite easy to the problem solver. Understanding is the process of mapping an input from its original form to a more useful one. The simplest kind of mapping is “one-to-one”. In one-to-one mapping each different problems would lead to only one solution. But there are very few inputs which are one-to-one. Other mappings are quite difficult to implement. Many-to-one mappings are frequent is that free variation is often allowed, either because of the physical limitations of that produces the inputs or because such variation simply makes the task of generating the inputs. Many-to-one mapping require that the understanding system know about all the ways that a target representation can be expressed in the source language. One-to-many mapping requires a great deal of domain knowledge in order to make the correct choice among the available target representation. The mapping process is simplest if each component can be mapped without concern for the other components of the statement. If the number of interactions increases, then the complexity of the problem will increase. In many understanding situations the input to which meaning should be assigned is not always the input that is presented to the under stander. Because of the complex environment in which understanding usually occurs, other things often interfere with the basic input before it reaches the under stander. Hence the understanding will be more complex if there will be some sort of noise on the inputs.