Artificial Intelligence and Soft Computing: Behavioral ... - Arteimi.info

“chair”. A specialization rule may employ one or more of the following
operators:
i) Replacing variables by constants; for instance, color
(red) could be specialized to color (ball, red).
ii) Adding condition to a conjunctive expression; for
example, in the concept of chair, we may add one or
more conjunctive terms like has-a-slant-surface-of
(chair).
iii) Eliminating a disjunctive literal from an expression; for
example, one can eliminate Color (x, red) from Color
(X, red) ∨ Size (X, large), to specialize a rule.
iv) Replacing a property with its child in its class hierarchy;
for example, if we know primary color is a super-class
of (green) then we can replace color (x, primary color)
by color (x, green), for specializing a rule.
Definition 13.13: A generalization of a set of rules is a rule that can group
a set of classes (sub-classes) into a super-class (class) by employing inverse
operators, corresponding to those defined in specialization rule. Formally, the
operators are:
i) Replacing constants by variables,
ii) Deleting a condition from conjunctive expressions,
iii) Adding a disjunctive literal to an expression, and
iv) Replacing a property with its parent in a class hierarchy.
Definition 13.14: The constructive generalization is a generalization of
the rules with the additional relations, not available in the existing instances.
For example, if block A is on the table, block B is on A and block C is on B,
we can write
On (A , table) ∧ On (B, A) ∧ On (C, B),
from which we can generalize, topmost block (C) ∧ bottommost block (A),
which are not present in the previous descriptions.
Definition 13.15: Inductive bias is defined as a set of factors that influence
the selection of hypothesis, excluding those factors that are directly related to
the training instances. There exist two types of bias in general: i) restricting
hypothesis from the hypotheses space and ii) the use of a preferential ordering
among the hypotheses [11].