Problem Characteristics in Artificial Intelligence, Unit -2 Problem Solving and Searching Techniques o choose an appropriate method for a particular problem first we need to categorize the problem based on the following characteristics. Is the problem decomposable into small sub-problems which are easy to solve? Can solution steps be ignored or undone? Is the universe of the problem is predictable? Is a good solution to the problem is absolute or relative? Is the solution to the problem a state or a path? What is the role of knowledge in solving a problem using artificial intelligence? Does the task of solving a problem require human interaction? 1. Is the problem decomposable into small sub-problems which are easy to solve? Can the problem be broken down into smaller problems to be solved independently? See also Water Jug Problem in Artificial Intelligence The decomposable problem can be solved easily. Example: In this case, the problem is divided into smaller problems. The smaller problems are solved independently. Finally, the result is merged to get the final result. Is the problem decomposable 2. Can solution steps be ignored or undone? In the Theorem Proving problem, a lemma that has been proved can be ignored for the next steps. Such problems are called Ignorable problems. In the 8-Puzzle, Moves can be undone and backtracked. Such problems are called Recoverable problems. In Playing Chess, moves can be retracted. Such problems are called Irrecoverable problems. Ignorable problems can be solved using a simple control structure that never backtracks. Recoverable problems can be solved using backtracking. Irrecoverable problems can be solved by recoverable style methods via planning. 3. Is the universe of the problem is predictable? In Playing Bridge, We cannot know exactly where all the cards are or what the other players will do on their turns. Uncertain outcome! For certain-outcome problems, planning can be used to generate a sequence of operators that is guaranteed to lead to a solution. For uncertain-outcome problems, a sequence of generated operators can only have a good probability of leading to a solution. Plan revision is made as the plan is carried out and the necessary feedback is provided. 4. Is a good solution to the problem is absolute or relative? The Travelling Salesman Problem, we have to try all paths to find the shortest one. See also Generate and Test Heuristic Search - Artificial Intelligence Any path problem can be solved using heuristics that suggest good paths to explore. For best-path problems, a much more exhaustive search will be performed. 5. Is the solution to the problem a state or a path The Water Jug Problem, the path that leads to the goal must be reported.

1. Presentation
on
By
BHARAT BHUSHAN
Asst. Professor, Department of Computer Sc.
RLSY College, Ranchi
Buddha Science and Technical Institute, Ranchi
www.bharatsir.com
Production Systems in
Artificial Intelligence

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Artificial Intelligence
Production Systems
A production system is a kind of cognitive
architecture that is used to implement search
algorithms and replicate human problem-
solving skills. This problem-solving
knowledge is encoded in the system in the
form of little quanta popularly known as
productions.
It consists of two components:
rule and action.

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Artificial Intelligence
Rules recognize the condition, and the
actions part has the knowledge of how to
deal with the condition.
In simpler words, the production system in
AI contains a set of rules which are defined
by the left side and right side of the system.
The left side contains a set of things to watch
for (condition), and the right side contains
the things to do (action).

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Artificial Intelligence
Elements of a Production System
An AI production system has three main elements
which are as follows:
Global Database: The primary database which
contains all the information necessary to
successfully complete a task. It is further broken
down into two parts: temporary and permanent.
The temporary part contains information relevant
to the current situation only whereas the
permanent part contains information about the
fixed actions.

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Artificial Intelligence
A Set of Production Rules: A set of rules that
operates on the global database. Each rule consists
of a precondition and post condition that the
global database either meets or not. For example,
if a condition is met by the global database, then
the production rule is applied successfully.
Control System: A control system that acts as the
decision-maker, decides which production rule
should be applied. The Control system stops
computation or processing when a termination
condition is met on the database.

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Artificial Intelligence
Characteristics of a Production System
A production system has the following features:
Simplicity: Due to the use of the IF-THEN
structure, each sentence is unique in the
production system. This uniqueness makes the
knowledge representation simple to enhance the
readability of the production rules.
Modularity: The knowledge available is coded in
discrete pieces by the production system, which
makes it easy to add, modify, or delete the
information without any side effects.

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Artificial Intelligence
Modifiability: This feature allows for the
modification of the production rules. The
rules are first defined in the skeletal form
and then modified to suit an application.
Knowledge-intensive: As the name
suggests, the system only stores knowledge.
All the rules are written in the English
language. This type of representation solves
the semantics problem.

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Artificial Intelligence
Characteristics of Production System

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Artificial Intelligence
Classes of a Production System?
A production system is classified into four main
classes which are:
Monotonic Production System: In a monotonic
production system, the use of one rule never
prevents the involvement of another rule when
both the rules are selected at the same time.
Hence, it enables the system to apply rules
simultaneously.
Partially Commutative Production System: In
this production system if a set of rules is used to

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Artificial Intelligence
change state A to state B then any allowable
combination of these rules will also produce the
same results (convert state A to state B).
Non-Monotonic Production System: This
production system increases the problem-solving
efficiency of the machine by not keeping a record
of the changes made in the previous search
process. These types of production systems are
useful from an implementation point of view as
they do not backtrack to the previous state when it
is found that an incorrect path was followed.

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Artificial Intelligence
Commutative Production System: These type of
production systems is used when the order of
operation is not important, and the changes are
reversible.

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Artificial Intelligence
Advantages of Production System in AI
 Offers modularity as all the rules can be added,
deleted, or modified individually.
 Separate control system and knowledge base.
 An excellent and feasible model that imitates
human problem-solving skills.
 Beneficial in real-time applications and
environment.
 Offers language independence.

13. Bharat Bhushan, Assistant Professor, RLSY College, Ranchi
Artificial Intelligence