Browsing by Author "Zangari, Jessica"

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Design and implementation of a modern ASP grounder
(2018-01-19) Zangari, Jessica; Leone, Nicola; Calimeri, Francesco; Perri, Simona
Answer Set Programming (ASP) is a declarative programming paradigm proposed in the area of non-monotonic reasoning and logic programming in the late '80 and early '90. Thanks to its expressivity and capability of dealing with incomplete knowledge, ASP that became widely used in AI and recognized as a powerful tool for Knowledge Representation and Reasoning (KRR). On the other hand, its high expressivity comes at the price of a high computational cost, thus requiring reliable and high-performance implementations. Throughout the years, a signi cant e ort has been spent in order to de ne techniques for an e cient computation of its semantics. In turn, the availability of e cient ASP systems made ASP a powerful tool for developing advanced applications in many research areas as well as in industrial contexts. Furthermore, a signi cant amount of work has been carried out in order to extend the basic language and ease knowledge representation tasks with ASP, and recently a standard input language, namely ASP-Core-2, has been de ned, also with the aim of fostering interoperability among ASP systems. Although di erent approaches for the evaluation of ASP logic programs have been proposed, the canonical approach, which is adopted in mainstream ASP systems, mimics the de nition of answer set semantics by relying on a grounding module (grounder), that generates a propositional theory semantically equivalent to the input program, coupled with a subsequent module (solver ) that applies propositional techniques for generating its answer sets. The former phase, called grounding or instantiation, plays a key role for the successful deployment in real-world contexts, as in general the produced ground program is potentially of exponential size with respect to the input program, and therefore the subsequent solving step, in the worst case, takes exponential time in the size of the input. To mitigate these issues, modern grounders employ smart procedures to obtain ground programs signi cantly smaller than the theoretical instantiation, in general. This thesis focuses on the ex-novo design and implementation of a new modern and e cient ASP instantiator. To this end, we study a series of techniques geared towards the optimization of the grounding process, questioning the techniques employed by modern grounders with the aim of improving them and introducing further optimization strategies, which lend themselves to the integration into a generic grounder module of a traditional ASP system following a ground & solve approach. In particular, we herein present the novel system I-DLV that incorporates all these techniques leveraging on their synergy to perform an e cient instantiation. The system features full support to ASP-Core-2 standard language, advanced exibility and customizability mechanisms, and is endowed with extensible design that eases the incorporation of language upi dates and optimization techniques. Moreover, its usage is twofold: besides being a stand-alone grounder, it is also a full- edged deductive database engine. In addition, along with the solver wasp it has been integrated in the new version of the widespread ASP system DLV recently released.
Design and Implementation of an ASP-based Stream Reasoner
(Università della Calabria, 2023-07-04) Mastria, Elena; Calimeri, Francesco; Perri, Simona; Zangari, Jessica
Stream Reasoning (SR) is a relatively young research field that evolved from Stream Processing (SP) more than a decade ago. It focuses on studying and developing advanced approaches and techniques for the continuous application of inference techniques to highly dynamic data streams. Data streams are (theoretically) infinite streams of information that dynamically change over time. These are generated by sources (e.g., sensors, devices, social networks, etc.) that monitor a physical or virtual environment, continuously reporting the relative state and changes. While SP aims at quickly processing data streams while answering continuous queries on their elements, SR tackles inferencing new information taking into account the content of data streams along with background knowledge on the application domain. Recently, SR has been studied in several fields, and has become more and more relevant in diverse application scenarios, such as IoT, Smart Cities, Emergency Management, and Healthcare. In such types of context, applications require complex query answering in a minimal amount of time. This amount is defined from the application domain at hand and is typically real-time (< 1 second) or near real-time(< 1 minute). Therefore, an SR system (i.e., stream reasoner) must be able to perform complex reasoning tasks while efficiently processing heterogeneous data streams together with large background knowledge bases. Different SR approaches have been proposed in fields such as Data Stream Management Systems (DSMS), Complex Event Processing (CEP), Semantic Web, and Knowledge Representation and Reasoning (KRR). Among declarative KRR paradigms, Answer Set Programming (ASP) is a well-established formalism developed in the area of logic programming and non-monotonic reasoning. Thanks to the availability of robust and efficient implementations, ASP is successfully employed outside of academia to implement several real-world applications. Recently, ASP gained attention as a basis for SR, and significant steps in this direction have been taken. Several ASP-based solutions have been proposed: some combining SP and ASP implementations into a single engine, others natively extending ASP with SR constructs. However, existing ASP-based stream reasoners appear not mature enough concerning the desirable requirements for SR. This thesis focuses on designing and implementing a novel, reliable ASPbased stream reasoner. The main goal is to obtain a system featuring the following properties: (i) efficiently scale over real-world application domains; (ii) support a language that inherits the highly declarative nature and ease of use from ASP; (iii) easily extendable with new constructs that are relevant for practical SR scenarios. Therefore, we herein present the stream reasoner I-DLVsr. The input language is a straightforward extension of ASP with constructs to reason over data streams. The implementation relies on a tight interaction between two state-of-the-art solutions in ASP and SP: I2-DLV and Apache Flink, respectively. We tested I-DLV-sr on several real-world and synthetic domains to explore its capabilities in modeling SR scenarios and assess its performance. In the conducted experiments, the system obtained good results, proving the viability of the proposed approach and the robustness of the implementation herein presented.
Reasoning in highly dynamic environments
(Università della Calabria, 2021-07-03) Pacenza, Francesco; Greco, Gianluigi; Ianni, Giovambattista; Zangari, Jessica