AT4WS09 slide-21

GOOP is Good for Defeasible Planning

Assumptions modeled as provable assignments for an operator:

((assignment "MatchOnEffect" %%Rule Consequent%%
(?ws ?fluent ?listofpairs ?state ?preceding-state ) %% Plan assignment statement%%
("Assume" ?state (?prop ?value))) %%Statement of assumption%%
⇐ ... %%Rule antecedents%%
(Output ?ws ?prop ?value)
(Selectable ?ws ?prop))

Contingencies explict part of the Redux model.

For each appropriate operator, prove that each possible output that is one of the possible-output-values and not the one that was selectable is a contingency.
When such a contingency is asserted, Redux dependencies ensure that this part of the plan becomes invalid and goals need to be re-satisfied by re-planning.
GOOP program goal-regression algorithm with resequencing to get a planner.