Augmenting Stream Constraint Programming with Eventuality Conditions

TL;DR

This paper enhances stream constraint programming by introducing the 'until' constraint and '@' operator, improving expressiveness and efficiency for planning problems, with proven algorithms and competitive experimental results.

Contribution

It introduces novel 'until' and '@' constructs with efficient solving algorithms, expanding the framework's expressiveness for planning applications.

Findings

New constructs improve expressiveness for planning.

Algorithms are proven correct and efficient.

Competitive results on logic puzzles and path planning.

Abstract

Stream constraint programming is a recent addition to the family of constraint programming frameworks, where variable domains are sets of infinite streams over finite alphabets. Previous works showed promising results for its applicability to real-world planning and control problems. In this paper, motivated by the modelling of planning applications, we improve the expressiveness of the framework by introducing 1) the "until" constraint, a new construct that is adapted from Linear Temporal Logic and 2) the @ operator on streams, a syntactic sugar for which we provide a more efficient solving algorithm over simple desugaring. For both constructs, we propose corresponding novel solving algorithms and prove their correctness. We present competitive experimental results on the Missionaries and Cannibals logic puzzle and a standard path planning application on the grid, by comparing with Apt and Brand's method for verifying eventuality conditions using a CP approach.