Shared aggregate sets in answer set programming

TL;DR

This paper introduces new data structures and techniques for handling aggregates in answer set programming, reducing memory use and potentially improving solver performance by avoiding redundant computations.

Contribution

It proposes novel data structures and methods to efficiently manage aggregates involving undefined literals, enhancing solver efficiency and memory usage.

Findings

Reduced memory footprint in solvers

Improved solver performance through new propagation techniques

Empirical evidence supports the effectiveness of the approach

Abstract

Aggregates are among the most frequently used linguistic extensions of answer set programming. The result of an aggregation may introduce new constants during the instantiation of the input program, a feature known as value invention. When the aggregation involves literals whose truth value is undefined at instantiation time, modern grounders introduce several instances of the aggregate, one for each possible interpretation of the undefined literals. This paper introduces new data structures and techniques to handle such cases, and more in general aggregations on the same aggregate set identified in the ground program in input. The proposed solution reduces the memory footprint of the solver without sacrificing efficiency. On the contrary, the performance of the solver may improve thanks to the addition of some simple entailed clauses which are not easily discovered otherwise, and since redundant computation is avoided during propagation. Empirical evidence of the potential impact of the proposed solution is given. (Under consideration for acceptance in TPLP).