Fine-Grained Diagnostics of Ontologies with Assurance - Efficient Decision Support Systems: Practice and Challenges from Current to Future - page 85

fire in a building which is supported through a fire alarm system. Possible actions (states) of
the system turn off the electricity and then to pump water. After just having turned off the
electricity, it does not extinguish the fire, but only the pumping of water guarantees that it
is really extinguished. Using the following guess and check programs fire guess and fire check
respectively, we can compute a plan for extinguishing the fire by two actions, fire guess and
fire check , the program fire guess guesses all candidate plans P

=

p 1 , p 2 , ..., p n using time points

for action execution,

fire_guess:
% Timestamps:
time(0).
time(1).
% Guess a plan:
turn_off(T) v -pump(T) :- time(T).
pump(T) v -pump(T) :- time(T).
% Forbid concurrent actions:
:- pump(T), turn_off(T).
while fire check checks whether any such plan P is conformant for the goal g

=

( ) not extinguished The final constraint eliminates a plan execution if it reaches the goal; thus,

fire check has no answer set if the plan P is conformant.
fire_check:
% Initial state:
fired(0) v -fired(0).
% Frame Axioms:
fired(T1) :- fired(T),
time(T),
not -fired(T1),
T1=T+1.
turned_off(T1) :- turn_off(T),
T1=T+1.
% Effect of turning off:
turned_off(T1) :- turn_off(T),
T1=T+1.
fired(T1) v -fired(T1) :- turn_off(T),
fired(T),
T1=T+1.

2

% Effect of pumping:
-fired(T1) :- pump(T),
turn_off(T),
T1=T+1.
% Check goal in stage 2 (constraint):
:- not fired(2).
The program fire guess generates the answer set S

= {

time

(

0

)

, time

(

1

)

, turn off ( 0

)

, pump

(

1

) }

which corresponds to the (single) conformant plan

{

P

=

turn off , pump

}

for goal not

. Using the method fire guess and fire check can be integrated automatically into a single
program fire solve =

fired

(

2

)

fire check It has a single answer set, corresponding to the single

∨ fire guess

conformant plan P as desired.

With these examples in mind, we now turn to the problem of diagnosing such ontologies.
As should have become evident by now, spotting an error in a large-scale program is a
challenging task. We deliver a solution that is flexible and can be implemented with widely
standard components. In particular, our proposal does not require substantial changes to an

= {

turn off , pump

}