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

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Rule 1: If On (X, Y)<br />

Clear (X)<br />

Clear (Z)<br />

Add List: On (X, Z)<br />

Clear (Y)<br />

Delete List: On (X,Y)<br />

Clear (X)<br />

Rule 2: If On (X,Y)<br />

Clear (X)<br />

Add List: On (X, Table)<br />

Clear (Y)<br />

Delete List: On (X, Y)<br />

Rule 3: If On (X, Table)<br />

Clear (X)<br />

Clear (Z)<br />

Add List: On(X, Z)<br />

Delete List: Clear (Z)<br />

On (X, Table)<br />

We can try to solve the above problem by the following sequencing of<br />

operators. Rule 2 is applied to the initial problem state with an instantiation of X<br />

=A <strong>and</strong> Y =B to generate state S1 (fig. 12.4). Then we apply Rule 3 with an<br />

instantiation of X =B <strong>and</strong> Z =A to generate state S2. Next Rule 3 is applied once<br />

again to state S2 with an instantiation of X =C <strong>and</strong> Z =B to yield the goal state.<br />

Generating the goal from the given initial state by application of a sequence of<br />

operators causes expansion of many intermediate states. So, forward reasoning is<br />

not appropriate for such problems. Let us try to explore the problem through<br />

backward reasoning.<br />

12.2.1 Planning by Backward Reasoning<br />

Much effort can be saved, if we generate a plan for the current problem by<br />

backward reasoning. While planning through backward reasoning, we should<br />

check the required preconditions to satisfy a given goal. Further, to satisfy<br />

new sub-goals generated, we should check the existence of their preconditions<br />

in the ADD-list of rules, which on firing generate the sub-goals. To illustrate

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