Page 247 - DCAP310_INTRODUCTION_TO_ARTIFICIAL_INTELLIGENCE_AND_EXPERT_SYSTEMS
P. 247
Unit 13: Expert System Architecture
If the task is to prove that D is true, given A and B are true. According to forward chaining, start Notes
with Rule 1 and go on downward till a rule that fires is found. Rule 3 is the only one that fires in
the first iteration. After the first iteration, it can be concluded that A, B, and X are true. The second
iteration uses this valuable information. After the second iteration, Rule 2 fires adding Z is true,
which in turn helps Rule 4 to fire, proving that D is true. Forward chaining strategy is especially
appropriate in situations where data are expensive to collect, but few in quantity. However,
special care is to be taken when these rules are constructed.
Self Assessment
State whether the following statements are true or false:
4. Expert knowledge is often represented in the form of rules or as data outside the computer.
5. Rule-based expert systems does not play an important role in modern intelligent systems
and their applications.
6. The purpose of the inference engine is to seek information and relationships from the
knowledge base.
13.3 Non-production System Architectures
A 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. These rules, termed productions, are a basic representation found useful in automated
planning, expert systems and action selection. A production system provides the mechanism
necessary to execute productions in order to achieve some goal for the system. Productions
consist of two parts: a sensory precondition (or “IF” statement) and an action (or “THEN”). If a
production’s precondition matches the current state of the world, then the production is said to
be triggered. If a production’s action is executed, it is said to have fired. A production system also
contains a database, sometimes called working memory, which maintains data about current
state or knowledge, and a rule interpreter.
!
Caution The rule interpreter must provide a mechanism for prioritizing productions
when more than one is triggered.
13.3.1 Associative or Semantic Networks
Example: This example shows a set of production rules for reversing a string from an
alphabet that does not contain the symbols “$” and “*” (which are used as marker symbols).
P1: $$ -> *
P2: *$ -> *
P3: *x -> x*
P4: * -> null & halt
P5: $xy -> y$x
P6: null -> $
In this example, production rules are chosen for testing according to their order in this production
list. For each rule, the input string is examined from left to right with a moving window to find
a match with the LHS of the production rule. When a match is found, the matched substring in
the input string is replaced with the RHS of the production rule. In this production system, x and
LOVELY PROFESSIONAL UNIVERSITY 241
