LITERASI EKONOMI, RASIONALITAS EKONOMI, DAN KELOMPOK TEMAN SEBAYA TERHADAP PERILAKU KONSUMTIF

Perilaku konsumtif merupakan perilaku individu memanfaatkan sumber daya yang ia miliki untuk memaksimalkan nilai guna atau utility terhadap suatu barang ataupun jasa. Penelitian ini bertujuan untuk mengetahui tingkat pengaruh dari variabel-variabel literasi ekonomi, rasionalitas ekonomi dan kelompok teman sebaya terhadap perilaku konsumtif mahasiswa pendidikan ekonomi universitas negeri malang. Jenis penelitian ini adalah penelitian asosiatif dengan jumlah responden 163 yang ditentukan dengan metode simple random sampling. Teknik pengumpulan data menggunakan angket. Alat pengumpulan data menggunakan kuesioner. Analisis data yang digunakan adalah regresi linier berganda. Hasil penelitian menunjukkan bahwa variabel literasi ekonomi, rasionalitas ekonomi, kelompok teman sebaya berpengaruh terhadap perilaku konsumtif. Berdasarkan koefisien determinasi, variabel literasi ekonomi, rasionalitas ekonomi, dan kelompok teman sebaya memberikan kontribusi sebesar 28,70% terhadap perilaku konsumtif mahasiswa pendidikan ekonomi universitas negeri malang. Berdasarkan hasil penelitian ini, kepada mahasiswa selaku subjek penelitian ini agar selalu meningkatkan kemampuannya dalam berperilaku secara ekonomis juga secara teoritis menjadi referensi untuk penelitian-penelitian selanjutnya

Computing Query Answering With Non-Monotonic Rules: A Case Study of Archaeology Qualitative Spatial Reasoning

International audienceThis paper deals with querying ontology-based knowledge bases equipped with non-monotonic rules through a case study within the framework of Cultural Heritage. It focuses on 3D underwater surveys on the Xlendi wreck which is represented by an OWL2 knowledge base with a large dataset. The paper aims at improving the interactions between the archaeologists and the knowledge base providing new queries that involve non-monotonic rules in order to perform qualitative spatial reasoning. To this end, the knowledge base initially represented in OWL2-QL is translated into an equivalent Answer Set Programming (ASP) program and is enriched with a set of non-monotonic ASP rules suitable to express default and exceptions. An ASP query answering approach is proposed and implemented. Furthermore due to the increased expressiveness of non-monotonic rules it provides spatial reasoning and spatial relations between artifacts query answering which is not possible with query answering languages such as SPARQL and SQWRL

Reasoning about Typicality and Probabilities in Preferential Description Logics

In this work we describe preferential Description Logics of typicality, a nonmonotonic extension of standard Description Logics by means of a typicality operator T allowing to extend a knowledge base with inclusions of the form T(C) v D, whose intuitive meaning is that normally/typically Cs are also Ds. This extension is based on a minimal model semantics corresponding to a notion of rational closure, built upon preferential models. We recall the basic concepts underlying preferential Description Logics. We also present two extensions of the preferential semantics: on the one hand, we consider probabilistic extensions, based on a distributed semantics that is suitable for tackling the problem of commonsense concept combination, on the other hand, we consider other strengthening of the rational closure semantics and construction to avoid the so-called blocking of property inheritance problem.Comment: 17 pages. arXiv admin note: text overlap with arXiv:1811.0236

A connection method for a defeasible extension of ALCH\mathcal{ALCH}

This paper proposes a connection method \`a la Bibel for an exception-tolerant family of description logics (DLs). As for the language, we assume the DL $\mathcal{ALCH}$ extended with two typicality operators: one on (complex) concepts and one on role names. The language is a variant of defeasible DLs, as broadly studied in the literature over the past decade, in which most of these can be embedded. We revisit the definition of the matrix representation of a knowledge base and establish the conditions for a given axiom to be provable. We show that the calculus terminates and is sound and complete w.r.t. a DL version of the preferential semantics widely adopted in non-monotonic reasoning

Defeasible RDFS via Rational Closure

In the field of non-monotonic logics, the notion of Rational Closure (RC) is acknowledged as a prominent approach. In recent years, RC has gained even more popularity in the context of Description Logics (DLs), the logic underpinning the semantic web standard ontology language OWL 2, whose main ingredients are classes and roles. In this work, we show how to integrate RC within the triple language RDFS, which together with OWL2 are the two major standard semantic web ontology languages. To do so, we start from $\rho df$, which is the logic behind RDFS, and then extend it to $\rho df_\bot$, allowing to state that two entities are incompatible. Eventually, we propose defeasible $\rho df_\bot$ via a typical RC construction. The main features of our approach are: (i) unlike most other approaches that add an extra non-monotone rule layer on top of monotone RDFS, defeasible $\rho df_\bot$ remains syntactically a triple language and is a simple extension of $\rho df_\bot$ by introducing some new predicate symbols with specific semantics. In particular, any RDFS reasoner/store may handle them as ordinary terms if it does not want to take account for the extra semantics of the new predicate symbols; (ii) the defeasible $\rho df_\bot$ entailment decision procedure is build on top of the $\rho df_\bot$ entailment decision procedure, which in turn is an extension of the one for $\rho df$ via some additional inference rules favouring an potential implementation; and (iii) defeasible $\rho df_\bot$ entailment can be decided in polynomial time.Comment: 47 pages. Preprint versio

Current and Future Challenges in Knowledge Representation and Reasoning

Knowledge Representation and Reasoning is a central, longstanding, and active area of Artificial Intelligence. Over the years it has evolved significantly; more recently it has been challenged and complemented by research in areas such as machine learning and reasoning under uncertainty. In July 2022 a Dagstuhl Perspectives workshop was held on Knowledge Representation and Reasoning. The goal of the workshop was to describe the state of the art in the field, including its relation with other areas, its shortcomings and strengths, together with recommendations for future progress. We developed this manifesto based on the presentations, panels, working groups, and discussions that took place at the Dagstuhl Workshop. It is a declaration of our views on Knowledge Representation: its origins, goals, milestones, and current foci; its relation to other disciplines, especially to Artificial Intelligence; and on its challenges, along with key priorities for the next decade

Principles of KLM-style Defeasible Description Logics

The past 25 years have seen many attempts to introduce defeasible-reasoning capabilities into a description logic setting. Many, if not most, of these attempts are based on preferential extensions of description logics, with a significant number of these, in turn, following the so-called KLM approach to defeasible reasoning initially advocated for propositional logic by Kraus, Lehmann, and Magidor. Each of these attempts has its own aim of investigating particular constructions and variants of the (KLM-style) preferential approach. Here our aim is to provide a comprehensive study of the formal foundations of preferential defeasible reasoning for description logics in the KLM tradition. We start by investigating a notion of defeasible subsumption in the spirit of defeasible conditionals as studied by Kraus, Lehmann, and Magidor in the propositional case. In particular, we consider a natural and intuitive semantics for defeasible subsumption, and we investigate KLM-style syntactic properties for both preferen- tial and rational subsumption. Our contribution includes two representation results linking our semantic constructions to the set of preferential and rational properties considered. Besides showing that our seman- tics is appropriate, these results pave the way for more effective decision procedures for defeasible reasoning in description logics. Indeed, we also analyse the problem of non-monotonic reasoning in description logics at the level of entailment and present an algorithm for the computation of rational closure of a defeasible knowledge base. Importantly, our algorithm relies completely on classical entailment and shows that the computational complexity of reasoning over defeasible knowledge bases is no worse than that of reasoning in the underlying classical DL ALC