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Production System & Its types
• Production system or production rule system is a
computer program typically used to provide some
form of artificial intelligence, which consists primarily
of a set of rules about behavior but it also includes
the mechanism necessary to follow those rules as
the system responds to states of the world.
Components of production system
– A set of rules of the form Ci → Ai
where Ci is the condition part and Ai is the action part.
The condition determines when a given rule is applied, and
the action determines what happens when it is applied.
– One or more knowledge databases that contain whatever
information is relevant for the given problem.
– The order in which the rules are applied to the database,
and provides a way of resolving any conflicts that can arise
when several rules match at once.
– A rule applier which is the computational system that
implements the control strategy and applies the rules.
Features of PS
• Control/Search
Strategies
• Good control strategy
should cause motion.
• Systematic
• efficient
Classes of Production System in Artificial
Intelligence
• Monotonic Production System: It’s a production 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: It’s a type of production system in which the
application of a 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
the monotonic partially communicative system.
• Non-Monotonic Production Systems: These are useful for solving ignorable problems. These
systems are important from an 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. This production system increases efficiency since it is not
necessary to keep track of the changes made in the search process.
• Commutative Systems: These are usually useful for problems in which changes occur but can
be reversed and in which the order of operation is not critical. Production systems that are
not usually 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 must be made at the
first attempt itself.
Monotonic Reasoning
• Monotonic Reasoning is the process that does not
change its direction or can say that it moves in the one
direction.
• Monotonic Reasoning will move in the same direction
continuously means it will either move in increasing
order or decrease.
• But since Monotonic Reasoning depends on knowledge
and facts, It will only increase and will never decrease in
this reasoning.
• Example:
– Sun rises in the East and sets in the West.
Non-monotonic Reasoning
• Non-monotonic Reasoning is the process that changes its
direction or values as the knowledge base increases.
• It is also known as NMR in Artificial Intelligence.
• Non-monotonic Reasoning will increase or decrease
based on the condition.
• Since that Non-monotonic Reasoning depends on
assumptions, It will change itself with improving
knowledge or facts.
• Example:
– Consider a bowl of water, If we put it on the stove and
turn the flame on it will obviously boil hot and as we
will turn off the flame it will cool down gradually.

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Production System Types & Features

  • 2. • Production system or production rule system is a computer program typically used to provide some form of artificial intelligence, which consists primarily of a set of rules about behavior but it also includes the mechanism necessary to follow those rules as the system responds to states of the world.
  • 3. Components of production system – A set of rules of the form Ci → Ai where Ci is the condition part and Ai is the action part. The condition determines when a given rule is applied, and the action determines what happens when it is applied. – One or more knowledge databases that contain whatever information is relevant for the given problem. – The order in which the rules are applied to the database, and provides a way of resolving any conflicts that can arise when several rules match at once. – A rule applier which is the computational system that implements the control strategy and applies the rules.
  • 4. Features of PS • Control/Search Strategies • Good control strategy should cause motion. • Systematic • efficient
  • 5. Classes of Production System in Artificial Intelligence • Monotonic Production System: It’s a production 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: It’s a type of production system in which the application of a 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 the monotonic partially communicative system. • Non-Monotonic Production Systems: These are useful for solving ignorable problems. These systems are important from an 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. This production system increases efficiency since it is not necessary to keep track of the changes made in the search process. • Commutative Systems: These are usually useful for problems in which changes occur but can be reversed and in which the order of operation is not critical. Production systems that are not usually 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 must be made at the first attempt itself.
  • 6. Monotonic Reasoning • Monotonic Reasoning is the process that does not change its direction or can say that it moves in the one direction. • Monotonic Reasoning will move in the same direction continuously means it will either move in increasing order or decrease. • But since Monotonic Reasoning depends on knowledge and facts, It will only increase and will never decrease in this reasoning. • Example: – Sun rises in the East and sets in the West.
  • 7. Non-monotonic Reasoning • Non-monotonic Reasoning is the process that changes its direction or values as the knowledge base increases. • It is also known as NMR in Artificial Intelligence. • Non-monotonic Reasoning will increase or decrease based on the condition. • Since that Non-monotonic Reasoning depends on assumptions, It will change itself with improving knowledge or facts. • Example: – Consider a bowl of water, If we put it on the stove and turn the flame on it will obviously boil hot and as we will turn off the flame it will cool down gradually.