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Planner Assumption 2: Do Parameter Settings Matter to a Fair Comparison?

In this planner set, only three have obvious, easily manipulable parameters: Blackbox, HSP and UCPOP. blackbox has an extensive set of parameters that control everything from how much trace information to print to the sequence of solver applications. HSP's function can be varied to include (or not) loop detection, change the search heuristic and vary the number paths to expand. For UCPOP, the user can change the strategies governing node orderings and flaw selection.

We did not run any experiments for this assumption because not all of the planners have parameters and because it is clear from the literature that the parameters do matter. Blackbox relies heavily on random restarts and trying alternative SAT solvers. In Kautz and Selman (1999), the authors of blackbox carefully study aspects of blackbox's design and demonstrate differential performance using different SAT solvers; they propose hypotheses for the performance differences and are working on better models of performance variation.

At the heart of HSP is heuristic search. Thus, its performance varies depending on the heuristics. Experiments with both HSP and FF (a planner that builds on some ideas from HSP) have shown the importance of heuristic selection in search space expansion, computation time and problem scale up [Haslum Geffner 2000,Hoffmann Nebel 2001].

As with HSP, heuristic search is critical to UCPOP's performance. A set of studies have explored alternative settings to the flaw selection heuristics employed by UCPOP [Joslin Pollack 1994,Srinivasan Howe 1995,Genevini Schubert 1996], producing dramatic improvements on some domains with some heuristics. As Pollack et al. (1997) confirmed, a good default strategy could be derived, but its performance was not the best under some circumstances.

Thus, because parameters can control fundamental aspects of algorithms, such as their search strategies, the role of parameters in comparisons cannot be easily dismissed.


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