[Chair]  [Computer Science Department (FBI)]  [University Dortmund] 

Introductory Talk

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ModPlan - Modern Action Planning


Domain Encoding

A pure propositional encoding can have efficiency drawbacks during the exploration. A multivariate representation for the atom set is often preferable. In the SAS+ encoding, groups of mutually exclusive atoms are generated. This encoding serves as an optional input for existing planners that can exploit this facility.

The output file format for this domain analysis step is a Lisp-like representation of the set of reachable atoms and their partitioning into SAS+ variable domains.

In planning with pattern databases, the automated selection of possible abstraction functions to yield informative pattern databases is a hard combinatorial task. This is especially true for the creation of disjoint databases, in which operator projections are void in all but one abstraction. In plannning, pattern database abstraction are most effective if they consider SAS+ groups in common.

Knowledge Acquisition

There are different bin-packing approximation algorithms that infer a partitioning of variable groups before constructing the databases. The maximum size of a pattern database is bounded by the multiplication of the cardinalities of the selected variable domains.

Knowledge Engineering

Even though we are currently working at a genetic algorithm to improve the first partition of groups, domain expert guidance in this optimization process is crucial. The expert is asked to refine the approximated, disjoint partitioning into planning pattern databases proposed in the inference module, by modifying the SAS+ partition for the different pattern databases in an XML frontend.
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