Problem Solving In AI

Problem solving, particularly in artificial intelligence, may be characterized as a systematic search through a range of possible actions in order to reach some predefined goal or solution. Problem-solving methods divide into special purpose and general purpose. A special-purpose method is tailor-made for a particular problem and often exploits very specific features of the situation in which the problem is embedded. In contrast, a general-purpose method is applicable to a wide variety of problems. One general-purpose technique used in AI is means-end analysis—a step-by-step, or incremental, reduction of the difference between the current state and the final goal. The program selects actions from a list of means—in the case of a simple robot this might consist of PICKUP, PUTDOWN, MOVEFORWARD, MOVEBACK, MOVELEFT, and MOVERIGHT—until the goal is reached.

Artificial Intelligence- in contrast with conventional problem solving techniques such as operation research, management science, or decision support systems-employ basically blind and heuristic approaches.

Blind Search: A blind search (also called an uninformed search) is a search that has no information about its domain. The only thing that a blind search can do is distinguish a non-goal state from a goal state.

Breadth-First Search: Using a breadth-first strategy we expand the root level first and then we expand all those nodes (i.e. those at level 1) before we expand any nodes at level 2.

Depth-First Search: Depth first search explores one branch of a tree before it starts to explore another branch. It can be implemented by adding newly expanded nodes at the front of the queue.

Heuristic Search:

A Heuristic is an operationally-effective nugget of information on how to direct search in a problem space. Heuristics are only approximately correct. Their purpose is to minimize search on average.Heuristic search is much faster and cheaper than a blind search. The results are considered good enough, and in the case of quantitative analysis they are very close to optimal solutions.

Characteristics:

Learns more by acting than analyzing the situation and places more emphasis on feedback

Uses trial and error and spontaneous action

Uses common sense, intuition and feelings

Looks for highly visible situational differences that vary with time

References: Wikipedia, Class Materials

Introducing AI

While discussing about Artificial Intelligence, the most important thing is to understand the basic concept of it. It applies to a computer system that is able to operate in a manner similar to that of human intelligence; that is, it can understand natural language and is capable of solving problems, learning, adapting, recognizing, classifying, self-improvement, and reasoning.

But Why AI? The goal of research on artificial intelligence is to understand the nature of thought and intelligent behavior and to design intelligent systems. A computer is not really intelligent; it just follows directions very quickly. At the same time, it is the speed and memory of modern computers that allows researchers to manage the huge quantities of data necessary to model human thought and behavior. An intelligent machine would be more flexible than a computer and would engage in the kind of "thinking" that people actually do. According to the famous Turing Test, proposed in 1950 by British mathematician and logician Alan Turing, a machine would be considered intelligent if it could convince human observers that another human, rather than a machine, was answering their questions in conversation.

Branches of AI:

Some of these may be regarded as concepts or topics rather than full branches.logical AI, search, pattern recognition, representation, inference, common sense knowledge and reasoning, learning from experience, planning, epistemology, ontology, heuristics, genetic programming

Applications of AI:

Game playing, speech recognition, understanding natural language, computer vision, expert systems, heuristic classification.

Areas: Defense, Transportation, Medicine, Manufacturing, Entertainment

Recent Updates:

Fuel injection systems in our cars use learning algorithms. Jet turbines are designed using genetic algorithms. Every cell phone call and e-mail is routed using artificial intelligence,

Future:

Within 30 years, Dr Brooks believes that we will have an understanding of how the human brain works that will give us "templates of intelligence" for developing strong AI and that by 2050, our lives will be populated with all kinds of intelligent robots.

Reference : http://news.bbc.co.uk/1/hi/in_depth/sci_tech/2001/artificial_intelligence/1555742.stm