Exploiting Partial Knowledge in Declarative Domain-Specific Heuristics for ASP

TL;DR

This paper introduces a new semantics for declarative domain-specific heuristics in ASP, enabling more effective solving of large industrial problems by evaluating heuristics on partial solutions.

Contribution

It proposes a novel semantics allowing negation as failure and aggregates in heuristics to be evaluated on partial states, and implements this in the Alpha ASP system.

Findings

Enhanced solving of industrial-size problems

First implementation of declarative heuristics in lazy-grounding ASP

Improved efficiency with new heuristics in ASP solving

Abstract

Domain-specific heuristics are an important technique for solving combinatorial problems efficiently. We propose a novel semantics for declarative specifications of domain-specific heuristics in Answer Set Programming (ASP). Decision procedures that are based on a partial solution are a frequent ingredient of existing domain-specific heuristics, e.g., for placing an item that has not been placed yet in bin packing. Therefore, in our novel semantics negation as failure and aggregates in heuristic conditions are evaluated on a partial solver state. State-of-the-art solvers do not allow such a declarative specification. Our implementation in the lazy-grounding ASP system Alpha supports heuristic directives under this semantics. By that, we also provide the first implementation for incorporating declaratively specified domain-specific heuristics in a lazy-grounding setting. Experiments confirm that the combination of ASP solving with lazy grounding and our novel heuristics can be a vital ingredient for solving industrial-size problems.