
| Name          | Order   | STRIPS Limit   | Durative Limit   |
|---------------|---------|----------------|------------------|
| MW-Loc        | 1       | 10000          | 12000            |
| MW-Loc-Conf   | 2       | 100000         | 100000           |
| LCFR-Loc      | 3       | 200000         | 240000           |
| LCFR-Loc-Conf | 4       | ∞              | ∞                |

1000 · 2 i−2 **additional nodes. The maximum number of nodes generated using a specific flaw**
selection strategy is 1000 · 2 i−1 after i **rounds. An optional upper limit on the number of**
generated search nodes can be set for each flaw selection strategy. This is useful for flaw selection strategies that typically solve problems quickly, when they solve them at all within reasonable time. Table 7 shows the search limits used by VHPOP **at IPC3. These limits**
were determined after some initial trials on the competition problems. Note that there was no set search limit for the last flaw selection strategy. Whenever the other three strategies all reached their search limits without having found a solution, LCFR-Loc-Conf was used until physical resource limits were reached.

Table 8 shows the number of plans generated in the STRIPS Satellite domain before a solution is found for the four flaw selection strategies used **at IPC3, and also the number** of generated plans when combining the four strategies using **the schedule in Table 7. To**
better understand how the round-robin scheduling works, we **take a closer look at the**
numbers for problem 15. Table 9 shows how the total number of generated plans is divided between rounds and flaw selection strategies. Note that although MW-Loc is actually the best strategy for this problem, it is stopped already in round 5. The total number of generated plans does not exactly match the actual number of generated plans reported in Table 8. This is because we only consider suspending the use of a flaw selection strategy after all refinements of the last selected plan have been added, so the limit in a round can be exceeded slightly in practice. The numbers in Table 9 represent an idealized situation where flaw selection strategies are switched when the number **of generated plans exactly**
matches the limit for the current round.

VHPOP solved 122 problems out of 224 attempted at IPC3. The quality **of the plans,**
in terms of number of steps, generated by VHPOP **was generally very high. For plain**
STRIPS domains, VHPOP**'s plans were typically within 10 percent of the best plans found** by any planner in the competition, with 28 of VHPOP**'s 68 STRIPS plans being at least as** short as the best plans found and, being a POCL planner, VHPOP **automatically exploits**
parallelism in planning domains, generating plans for STRIPS domains with low total plan execution time (Table 10). Table 11 shows that VHPOP **also performed well in terms of**
number of solved problems in four of the six STRIPS domains, being competitive with top performers such as MIPS and LPG **(particularly in the Rovers domain).**