Event Calculus Meets Hybrid ASP

2026-06-03

AI Summary

Traditional discrete Event Calculus suffers from combinatorial explosion and imprecise representation when handling continuous change and large-scale, dense temporal and fluent domains, while base-free approaches risk non-termination. This work proposes Hybrid Event Calculus (Hybrid EC), which unifies discrete and continuous change through functional fluents and an abstract time-step mechanism. By integrating hybrid ASP solvers such as Clingcon and clingo-lpx, Hybrid EC encodes fluents and time over dense domains as linear constraints delegated to external solvers. The approach guarantees termination while enabling precise modeling of continuous dynamics. Experimental results demonstrate that its performance remains insensitive to the scale of the value domain, and the use of rational numbers does not compromise scalability.

Abstract

Event Calculus (EC) implemented in answer set programming (ASP) has proven suitable for specifying requirements on safety-critical systems thanks to its elegant representation of both discrete and continuous changes and its semantic closeness to semi-formal natural language. However, continuous changes and the size of value domains of time and system properties (fluents) pose significant challenges. Grounding-based ASP solvers, e.g., clingo, which implement Discrete EC (DEC), lead to combinatorial explosion in program size and inaccurate representation. The grounding-free s(CASP) does not discretize but struggles with non-termination due to its top-down execution. This paper introduces Hybrid EC, an extended axiomatization of DEC, that tackles the challenges via functional fluents and a mapping of time to abstract steps. We implement it using clingcon and clingo-lpx (Hybrid ASP systems over integers and rationals, respectively) where the value (dense) domains of fluents and time are represented as linear constraints and evaluated by external solvers, while ensuring termination whenever solutions exist. We validate both implementations on a number of examples and observe that they are unaffected by the size of the domains and that handling rationals does not impact scalability. Most importantly, the ability of clingo-lpx to handle dense domains enables accurate modeling of continuous change.

Problem

• Event Calculus
• Answer Set Programming
• continuous change
• value domains
• non-termination

Innovation

• Hybrid Event Calculus
• Hybrid ASP
• continuous change
• functional fluents
• linear constraints