scholarly journals ASPMT(QS): Non-Monotonic Spatial Reasoning with Answer Set Programming Modulo Theories

Author(s):  
Przemysław Andrzej Wałęga ◽  
Mehul Bhatt ◽  
Carl Schultz
2018 ◽  
Vol 18 (3-4) ◽  
pp. 355-371 ◽  
Author(s):  
GEORGE BARYANNIS ◽  
ILIAS TACHMAZIDIS ◽  
SOTIRIS BATSAKIS ◽  
GRIGORIS ANTONIOU ◽  
MARIO ALVIANO ◽  
...  

AbstractSpatial information is often expressed using qualitative terms such as natural language expressions instead of coordinates; reasoning over such terms has several practical applications, such as bus routes planning. Representing and reasoning on trajectories is a specific case of qualitative spatial reasoning that focuses on moving objects and their paths. In this work, we propose two versions of a trajectory calculus based on the allowed properties over trajectories, where trajectories are defined as a sequence of non-overlapping regions of a partitioned map. More specifically, if a given trajectory is allowed to start and finish at the same region, 6 base relations are defined (TC-6). If a given trajectory should have different start and finish regions but cycles are allowed within, 10 base relations are defined (TC-10). Both versions of the calculus are implemented as ASP programs; we propose several different encodings, including a generalised program capable of encoding any qualitative calculus in ASP. All proposed encodings are experimentally evaluated using a real-world dataset. Experiment results show that the best performing implementation can scale up to an input of 250 trajectories for TC-6 and 150 trajectories for TC-10 for the problem of discovering a consistent configuration, a significant improvement compared to previous ASP implementations for similar qualitative spatial and temporal calculi.


Author(s):  
Pedro Cabalar ◽  
Paulo E. Santos

This paper introduces a new formalism for the automated solution of spatial scenarios involving strings and holed objects. In particular, we revisit a previous formalisation that allows string loops to be treated as holes, but make a substantial modification by removing a previous limitation that prevented a string to cross its own loops. The formalisation introduced in the present paper relies on string segments as basic entities and achieves a greater degree of elaboration tolerance by using inertia to describe those parts of the physical scenario that are unaffected by a given action. As a representation language, we have used Temporal Answer Set Programming since it provides a simple and natural way to deal with time and inertia while, at the same time, it is accompanied by the automated tool 'telingo' that allows a systematic testing of the effects of any sequence of actions. As an illustrative example, we have studied the African Ring puzzle, a problem involving loops crossed by a unique string, and provided the first formalisation of its solution, to the best of our knowledge.


2016 ◽  
Vol 17 (2) ◽  
pp. 205-225 ◽  
Author(s):  
PRZEMYSŁAW ANDRZEJ WAŁĘGA ◽  
CARL SCHULTZ ◽  
MEHUL BHATT

AbstractThe systematic modelling ofdynamic spatial systemsis 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.


2008 ◽  
Vol 9 (4) ◽  
pp. 1-53 ◽  
Author(s):  
Stijn Heymans ◽  
Davy Van Nieuwenborgh ◽  
Dirk Vermeir

2013 ◽  
Vol 29 (18) ◽  
pp. 2320-2326 ◽  
Author(s):  
Carito Guziolowski ◽  
Santiago Videla ◽  
Federica Eduati ◽  
Sven Thiele ◽  
Thomas Cokelaer ◽  
...  

2016 ◽  
Vol 16 (5-6) ◽  
pp. 800-816 ◽  
Author(s):  
DANIELA INCLEZAN

AbstractThis paper presents CoreALMlib, an $\mathscr{ALM}$ library of commonsense knowledge about dynamic domains. The library was obtained by translating part of the Component Library (CLib) into the modular action language $\mathscr{ALM}$. CLib consists of general reusable and composable commonsense concepts, selected based on a thorough study of ontological and lexical resources. Our translation targets CLibstates (i.e., fluents) and actions. The resulting $\mathscr{ALM}$ library contains the descriptions of 123 action classes grouped into 43 reusable modules that are organized into a hierarchy. It is made available online and of interest to researchers in the action language, answer-set programming, and natural language understanding communities. We believe that our translation has two main advantages over its CLib counterpart: (i) it specifies axioms about actions in a more elaboration tolerant and readable way, and (ii) it can be seamlessly integrated with ASP reasoning algorithms (e.g., for planning and postdiction). In contrast, axioms are described in CLib using STRIPS-like operators, and CLib's inference engine cannot handle planning nor postdiction.


AI Magazine ◽  
2016 ◽  
Vol 37 (3) ◽  
pp. 25-32 ◽  
Author(s):  
Benjamin Kaufmann ◽  
Nicola Leone ◽  
Simona Perri ◽  
Torsten Schaub

Answer set programming is a declarative problem solving paradigm that rests upon a workflow involving modeling, grounding, and solving. While the former is described by Gebser and Schaub (2016), we focus here on key issues in grounding, or how to systematically replace object variables by ground terms in a effective way, and solving, or how to compute the answer sets of a propositional logic program obtained by grounding.


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