Program Synthesis as Dependency Quantified Formula Modulo Theory

Given a specification φ(X, Y ) over inputs X and output Y and defined over a background theory T, the problem of program synthesis is to design a program f such that Y = f (X), satisfies the specification φ. Over the past decade, syntax-guided synthesis (SyGuS) has emerged as a dominant approach to program synthesis where in addition to the specification φ, the end-user also specifies a grammar L to aid the underlying synthesis engine. This paper investigates the feasibility of synthesis techniques without grammar, a sub-class defined as T constrained synthesis. We show that T-constrained synthesis can be reduced to DQF(T),i.e., to the problem of finding a witness of a dependency quantified formula modulo theory. When the underlying theory is the theory of bitvectors, the corresponding DQF problem can be further reduced to Dependency Quantified Boolean Formulas (DQBF). We rely on the progress in DQBF solving to design DQBF-based synthesizers that outperform the domain-specific program synthesis techniques; thereby positioning DQBF as a core representation language for program synthesis. Our empirical analysis shows that T-constrained synthesis can achieve significantly better performance than syntax-guided approaches. Furthermore, the general-purpose DQBF solvers perform on par with domain-specific synthesis techniques.

A Comprehensive Survey on Word Representation Models: From Classical to State-of-the-Art Word Representation Language Models

Word representation has always been an important research area in the history of natural language processing (NLP). Understanding such complex text data is imperative, given that it is rich in information and can be used widely across various applications. In this survey, we explore different word representation models and its power of expression, from the classical to modern-day state-of-the-art word representation language models (LMS). We describe a variety of text representation methods, and model designs have blossomed in the context of NLP, including SOTA LMs. These models can transform large volumes of text into effective vector representations capturing the same semantic information. Further, such representations can be utilized by various machine learning (ML) algorithms for a variety of NLP-related tasks. In the end, this survey briefly discusses the commonly used ML- and DL-based classifiers, evaluation metrics, and the applications of these word embeddings in different NLP tasks.

Deleuze and the Third World

The purpose of this essay is to discuss Deleuze and Guattari's concept of the Third World. For Deleuze and Guattari, however, the Third World is not only a geographical term, but also one that denotes the linguistic zones, another term of the minority. The essay argues that the concept of the Third World is related to minor literature, the minor or intense use of language. This ‘transcendental exercise’ of writing is an opposition to the initial purpose of language, namely representation. Language must escape from its normative usage, and then be liberated to a new spatio-temporality, in other words, the linguistic Third World zones. My conclusion is that the creation of Third World linguistic zones is the repetition of differences against the generalisation of representation, such as becoming non-human and non-European, not in imitation of the molar form of the animal or a non-continent extending terrestrial power into the ocean, but as the right way to invent the people missing in the Third World. Inventing the people of the Third World is the right condition in which alternative political subjects can be produced through desubjectification, not domestication, by capitalist axiomatics. In this way, Deleuze's political philosophy aims to use the virtual politics of the Third World to radicalise the actual representation of the existing Left.

An Ontology Representation Language for Multimedia Event Applications

This paper presents formalization of a new Multimedia Web Ontology Language (E-MOWL) to handle events with media depictions. The temporal, spatial and entity aspects that are implicitly linked to an event are represented through this language to model the context of events. The already existing Multimedia Web Ontology Language (MOWL) can be leveraged for perceptual modelling of a domain, where the concepts manifest into media patterns in the multimedia document and helps in semantic processing of the contents. The language E-MOWL provides a rich method for representing knowledge corresponding to a specific domain wherein the context specifies the intended meaning of each element of the domain of discourse; an element in different context may correspond to different functional role. The context information associated with an event ties the audiovisual data with event related aspects. All these aspects when considered altogether provide the evidence and contribute towards recognizing an event from multimedia documents. The language also enables reasoning with the uncertainty associated with the events and is organized in the form of Bayesian Network (BN). The media items that are semantically relevant can be assimilated together on the basis of their association with events. We have demonstrated the efficacy of our approach by utilizing an ontology for the entertainment category in news domain to offer an application \textit{news aggregation} and event-based book recommendations.

An Analysis of Commitments in Ontology Language Design

Multiple ontology languages have been developed over the years, which brings afore two key components: how to select the appropriate language for the task at hand and language design itself. This engineering step entails examining the ontological ‘commitments’ embedded into the language, which, in turn, demands for an insight into what the effects of philosophical viewpoints may be on the design of a representation language. But what are the sort of commitments one should be able to choose from that have an underlying philosophical point of view, and which philosophical stances have a knock-on effect on the specification or selection of an ontology language? In this paper, we provide a first step towards answering these questions. We identify and analyse ontological commitments embedded in logics, or that could be, and show that they have been taken in well-known ontology languages. This contributes to reflecting on the language as enabler or inhibitor to formally characterising an ontology or an ontological investigation, as well as the design of new ontology languages following the proposed design process.

Reasoning with Contextual Knowledge and Influence Diagrams

Influence diagrams (IDs) are well-known formalisms, which extend Bayesian networks to model decision situations under uncertainty. Although they are convenient as a decision theoretic tool, their knowledge representation ability is limited in capturing other crucial notions such as logical consistency. In this article, we complement IDs with the light-weight description logic (DL) EL to overcome such limitations. We consider a setup where DL axioms hold in some contexts, yet the actual context is uncertain. The framework benefits from the convenience of using DL as a domain knowledge representation language and the modelling strength of IDs to deal with decisions over contexts in the presence of contextual uncertainty. We define related reasoning problems and study their computational complexity.

Spatial Reasoning about String Loops and Holes in Temporal ASP

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.

Network Morphology

The morphological machinery of a language is at the service of syntax, but the service can be poor. A request may result in the wrong item (deponency), or in an item the syntax already has (syncretism), or in an abundance of choices (inflectional classes or morphological allomorphy). Network Morphology regulates the service by recreating the morphosyntactic space as a network of information sharing nodes, where sharing is through inheritance, and inheritance can be overridden to allow for the regular, irregular, and, crucially, the semiregular. The network expresses the system; the way the network can be accessed expresses possible deviations from the systematic. And so Network Morphology captures the semi-systematic nature of morphology. The key data used to illustrate Network Morphology are noun inflections in the West Slavonic language Lower Sorbian, which has three genders, a rich case system and three numbers. These data allow us to observe how Network Morphology handles inflectional allomorphy, syncretism, feature neutralization, and irregularity. Latin deponent verbs are used to illustrate a Network Morphology account of morphological mismatch, where morphosyntactic features used in the syntax are expressed by morphology regularly used for different features. The analysis points to a separation of syntax and morphology in the architecture of the grammar. An account is given of Russian nominal derivation which assumes such a separation, and is based on viewing derivational morphology as lexical relatedness. Areas of the framework receiving special focus include default inheritance, global and local inheritance, default inference, and orthogonal multiple inheritance. The various accounts presented are expressed in the lexical knowledge representation language DATR, due to Roger Evans and Gerald Gazdar.