Non-monotonic spatial reasoning with answer set programming modulo theories*†. Issue 2 (30th August 2016)

• Record Type: Journal Article
• Authors: WAŁĘGA, PRZEMYSŁAW ANDRZEJ; SCHULTZ, CARL; BHATT, MEHUL
• Is Part Of: Theory and practice of logic programming. Volume 17:Issue 2(2017)
• Page Start: 205
• Page End: 225
• Publication Date: 2016-08-30
• Subjects: non-monotonic spatial reasoning, -- answer set programming modulo theories, -- declarative spatial reasoning, -- dynamic spatial systems, -- reasoning about space, -- actions, -- and change; Logic programming -- Periodicals; Artificial intelligence -- Computer programs -- Periodicals; Constraint programming (Computer science) -- Periodicals; 005.115
• DOI: 10.1017/S1471068416000193
• Languages: English
• ISSNs: 1471-0684

Abstract

Abstract: The systematic modelling of dynamic spatial systems is a key requirement in a wide range of application areas such as commonsense cognitive robotics, computer-aided architecture design, and dynamic geographic information systems. We present Answer Set Programming Modulo Theories (ASPMT)(QS), a novel approach and fully implemented prototype for non-monotonic spatial reasoning — a crucial requirement within dynamic spatial systems — based on ASPMT. ASPMT(QS) consists of a (qualitative) spatial representation module (QS) and a method for turning tight ASPMT instances into Satisfiability Modulo Theories (SMT) instances in order to compute stable models by means of SMT solvers. We formalise and implement concepts of default spatial reasoning and spatial frame axioms. Spatial reasoning is performed by encoding spatial relations as systems of polynomial constraints, and solving via SMT with the theory of real non-linear arithmetic. We empirically evaluate ASPMT(QS) in comparison with other contemporary spatial reasoning systems both within and outside the context of logic programming. ASPMT(QS) is currently the only existing system that is capable of reasoning about indirect spatial effects (i.e., addressing the ramification problem), and integrating geometric and QS information within a non-monotonic spatial reasoning context.