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Like, the relaxed plan for the single unmodified planning graph, we
cannot aggregate state distances because all notion of separate
states is lost in forming the initial literal layer, thus we only
compute heuristics that do not aggregate state distances.
No State Aggregation:
- Max In classical planning, the maximum cost literal
is used to get a max heuristic, but we use formulas to describe our
belief states, so we take the maximum cost clause as the cost of the
belief state to find the max heuristic
. The maximum
cost clause of the belief state, with respect to a single planning
graph, is:
where the cost of a clause is:
Here we find the cheapest literal as the cost of each clause to find
the maximum cost clause. This is an underestimate of the closest
state to our current belief state.
- Sum Like the classical planning sum heuristic, we can
take the sum
of the costs of the clauses in our
belief state to estimate our belief state distance
This heuristic takes the summation of costs of literals in the
closest estimated state in the belief state, and is inadmissible
because there may be a single action that will support every clause,
and we could count it once for each clause.
- Level When we have mutexes on the planning graph, we
can compute a level heuristic
(without mutexes
the level heuristic is equivalent to the max heuristic). The level
heuristic maintains the admissibility of the max heuristic but
improves the lower bound by considering what level of the planning
graph all literals in a constituent are non-pairwise mutex. The
level heuristic is computed by taking the minimum among the
, of the first level (
) in the
planning graph where literals of
are present with none of
them marked pairwise mutex. Formally:
Next: Multiple Planning Graph Heuristics
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2006-05-26