Artificial Intelligence is the study of how to make computers do things at which at the movement people are better. - Its main aim is depend upon the situation to take the decisions automatically. - AI is the scientific research, this research will begin from past 30 years , its origin is JAPAN. - AI is the part of the Computer Science Concerned with designing, intelligent computer systems, that is systems that exhibits the characteristics we associate with intelligence in Human Behavior. Once again this definition will raise the following question. “Intelligent Behavior “, in view of the difficulty in defining the Intelligence, Let us try to characteristics that is a list of number of characteristics by which we can identify the Human Intelligence . - In AI problems that appear very little common, there are appropriate Techniques to solve these problems are called AI Techniques. A Production System is best suited AI Technique to solve the State Space Problems like Water Jug, and Missionaries and Cannibals. these problems consists of State, State Space and Goal State. State = Initial state of the Problem. State space = Intermediate States between Initial State and Goal State. Goal State = Final state of the problem. - to solve state space problems Production System is best suited AI Technique. A production system consists of rules and factors. Knowledge is encoded in a declarative from which comprises of a set of rules of the form and Control strategy. PRODUCTION SYSTEM SITUATION that implies ACTION. Example:- IF the initial state is a goal state THEN quit. The major components of an AI production system are i. A global database ii. A set of production rules and iii. A control system The goal database is the central data structure used by an AI production system. The production system. The production rules operate on the global database. Each rule has a precondition that is either satisfied or not by the database. If the precondition is satisfied, the rule can be applied. Application of the rule changes the database. The control system chooses which applicable rule should be applied and ceases computation when a termination condition on the database is satisfied. If several rules are to fire at the same time, the control system resolves the conflicts. Four classes of production systems:- 1. A monotonic production system 2. A non monotonic production system 3. A partially commutative production system 4. A commutative production system. Advantages of production systems:- 1. Production systems provide an excellent tool for structuring AI programs. 2. Production Systems are highly modular because the individual rules can be added, removed or modified independently. 3. The production rules are expressed in a natural form, so the statements contained in the knowledge base should the a recording of an expert thinking out loud. Disadvantages of Production Systems:-One important disadvantage is the fact that it may be very difficult analyse the flow of control within a production system because the individual rules don’t call each other. Production systems describe the operations that can be performed in a search for a solution to the problem. They can be classified as follows. Monotonic production system :- A system in which the application of a rule never prevents the later application of another rule, that could have also been applied at the time the first rule was selected. Partially commutative production system:- A production system in which the application of a particular sequence of rules transforms state X into state Y, then any permutation of those rules that is allowable also transforms state x into state Y. Theorem proving falls under monotonic partially communicative system. Blocks world and 8 puzzle problems like chemical analysis and synthesis come under monotonic, not partially commutative systems. Playing the game of bridge comes under non monotonic , not partially commutative system. For any problem, several production systems exist. Some will be efficient than others. Though it may seem that there is no relationship between kinds of problems and kinds of production systems, in practice there is a definite relationship. Partially commutative , monotonic production systems are useful for solving ignorable problems. These systems are important for man implementation standpoint because they can be implemented without the ability to backtrack to previous states, when it is discovered that an incorrect path was followed. Such systems increase the efficiency since it is not necessary to keep track of the changes made in the search process. Monotonic partially commutative systems are useful for problems in which changes occur but can be reversed and in which the order of operation is not critical (ex: 8 puzzle problem). Production systems that are not partially commutative are useful for many problems in which irreversible changes occur, such as chemical analysis. When dealing with such systems, the order in which operations are performed is very important and hence correct decisions have to be made at the first time itself.