Problem Solving Approach to Typical Al Problems

Problem Solving Approach to Typical Al Problems

AU May-14, Dec.-14

Problems are the issues which comes across any system. A solution is needed to solve that particular problem. Strong intelligence is required to solve such problems. Traditionally people think that the person who is able to solve more and more problems is more intelligent than others. It is always said that problem solving skills demonstrates intelligence hence it becomes a major aspect in artificial intelligence to solve the problems. In order to understand how exactly problem solving contributes to intelligence, one needs to find out how intelligent species solve problems.

The classical approach to solving a problem is quite simple in which, given a problem at hand hit and trial method is used to check for various solutions to that problem. This hit and trial approach usually works well for trivial problems and is referred to as the classical approach to problem solving.

Generate and Test

This is a technical name given to the classical way of solving problems where different combinations are generated to solve the problems, and the one which solves the problem is taken as the correct solution. The rest of the combinations that are considered as incorrect solution are destroyed.

Al Components that are required to solve problem

There are six major components of an artificial intelligence system. They are solely responsible for generating desired results for particular problem. These components are as follows,

1. Knowledge Representation: It is the major foundation of an artificial intelligence system. It is used for representing necessary knowledge so as to generate knowledge base with the help of which AI system can perform tasks and generate results.

2. Heuristic Searching Techniques: Usually while dealing with the problems the knowledge base keeps on growing and growing making it difficult to search in that knowledge base. To tackle with this challenge, heuristic searching techniques can be used which can provide results (because of certain criteria) efficiently in terms of time and memory usage.

3. Artificial Intelligence Hardware: Hardware compatibility is major concern when it comes to deploy software on machines. Hardware must be efficient to accommodate and produce desire results. Hardware components includes each and every machinery required spanning from memory to processor to communicating devices. Al systems incomplete without Al hardware.

4. Computer Vision and Pattern Recognition: AI programs capture the inputs on their own by generating a real world scenario with the help of this component. Sufficient and compatible hardware enables better patterns gathering that makes a useful knowledge base.

5. Natural Language Processing: This component processes or analyses written or spoken languages. Speech recognition is not sufficient to capture real world data. Acquiring the word sequence and parsing sentence into computer is not just sufficient to gain knowledge about environment for AI systems. Natural Language processing plays vital role in understanding of domain of text to AI systems.