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The Model Checking Integrated Planning System (MIPS) is a temporal leastcommitment heuristic search planner based on a flexible object-orientedworkbench architecture. Its design clearly separates explicit and symbolicdirected exploration algorithms from the set of on-line and off-line computedestimates and associated data structures. MIPS has shown distinguishedperformance in the last two international planning competitions. In the lastevent the description language was extended from pure propositional planning toinclude numerical state variables, action durations, and plan quality objectivefunctions. Plans were no longer sequences of actions but time-stampedschedules. As a participant of the fully automated track of the competition,MIPS has proven to be a general system; in each track and every benchmarkdomain it efficiently computed plans of remarkable quality. This articleintroduces and analyzes the most important algorithmic novelties that werenecessary to tackle the new layers of expressiveness in the benchmark problemsand to achieve a high level of performance. The extensions include criticalpath analysis of sequentially generated plans to generate corresponding optimalparallel plans. The linear time algorithm to compute the parallel plan bypassesknown NP hardness results for partial ordering by scheduling plans with respectto the set of actions and the imposed precedence relations. The efficiency ofthis algorithm also allows us to improve the exploration guidance: for eachencountered planning state the corresponding approximate sequential plan isscheduled. One major strength of MIPS is its static analysis phase that groundsand simplifies parameterized predicates, functions and operators, that infersknowledge to minimize the state description length, and that detects domainobject symmetries. The latter aspect is analyzed in detail. MIPS has beendeveloped to serve as a complete and optimal state space planner, withadmissible estimates, exploration engines and branching cuts. In thecompetition version, however, certain performance compromises had to be made,including floating point arithmetic, weighted heuristic search explorationaccording to an inadmissible estimate and parameterized optimization.

Taming Numbers and Durations in the Model Checking Integrated Planning System