Title: Grounding Recursive Aggregates, By Roland Kaminski - Abstract: Problem solving in Answer Set Programming consists of two steps, a first grounding phase, systematically replacing all variables by terms, and a second solving phase computing the stable models of the obtained ground program. An intricate part of both phases is the treatment of aggregates, which are popular language constructs that allow for expressing properties over sets. In this talk, we elaborate upon the treatment of aggre gates during grounding in gringo series 4. Consequently, our approach is applicable to grounding based on semi-naive database evaluation techniques. In particular, we provide a series of algorithms detailing the treatment of recursive aggregates and illustrate this by a running example.
Title: Default Negation for Datalog+/-, By Andreas Pieris - Abstract: The Datalog+/- family of expressive extensions of Datalog has recently been introduced as a new paradigm for query answering in the presence of ontologies. It extends plain Datalog by features such as existential quantification in rule-heads and, at the same time, restricts the rule syntax so as to achieve decidability and tractability w.r.t. the dataset. Although the obtained formalisms are expressive enough for capturing standard ontology languages based on description logics, they are not powerful enough for expressing default negation (a.k.a. negation as failure). The database and the KR communities have recognized the need for extending Datalog+/- with default negation. Adding negation to existing Datalog+/- languages is an intriguing new problem that gave rise to a flourishing research activity the last years. In this talk, we are going to give an overview of recent results on conjunctive query answering under the main Datalog+/- languages enriched with negation, focussing on the well-founded and stable model semantics.
Title: Logic, Policy Languages, and Relationship-Based Access Control, By Philip W.L. Fong - Abstract: Behind Facebook, Google+ and other social network systems is a paradigm of access control that bases authorization decisions on how the resource owner and the access requestor are related to one another. This paradigm, known as Relationship-Based Access Control (ReBAC), is found to be applicable not only in the domain of social computing, but also in other organizational settings such as electronic health records systems. In this talk, I will give an introduction to ReBAC, with an emphasis on how it gives rise to opportunities for applying various kinds of logic, including modal, hybrid and temporal logics, as policy languages to describe access control policies in ReBAC. If time permits, I will also survey a number of policy reasoning problems associated with ReBAC.
Title: Inference in Natural Language Understanding, By Jerry Hobbs - Abstract: We understand natural language discourse so well because we know so much. We are able to draw the inferences necessary to tie the various parts of a discourse together, and how we do this is perhaps the central problem in natural language understanding.In this talk I will show that many representational problems can be bypassed by reifying states and events, resulting in a very simple picture of compositional semantics. Then I will show how abduction, or finding the best explanation for the content of a text, solves a wide range of pragmatics problems, including coreference resolution, the interpretatiion of metonymy and metaphor, and the discovery of discourse structure. Finally I will discuss an effort to build an adequate knowledgel base for natural language understanding, by both manual and automatic means, in two areas --the structure of events and goal-directed behavior.
Title: Cognitive Programming, By Antonis Kakas - Abstract: Cognitive Programming is a computing paradigm emerging at the crossroads of Cognitive Psychology and Artificial Intelligence.It rests on the synthesis of knowledge from Cognitive Psychology about the structure and activation of human knowledge together with theoretical models and computational methods in Artificial Intelligence in order to provide a natural problem solving environment for ordinary common sense tasks. Cognitive Programming is strongly driven by the need for computer systems and applications that exhibits smart behavior for ordinary day to day human tasks. Such applications are generally in the form of Cognitive Assistants that, like a human personal assistant, can help their owner to make decisions that are attuned to the personal preferences of the owner, e.g. to seemingly manage the incoming calls of a user's mobile phone according to the current circumstances of the user and her/his personal preferences, or to focus the search on the Web via deeper and personalized understanding of the query posed by the user. The aim is for the programming framework to be naturally simple and highly resilient so that programming can be carried out by the users themselves without the need for any specialized programming skills. The talk will present the desirable characteristics of Cognitive Programming in contrast with conventional programming frameworks and the main challenges that these requirements pose. It will expose a new perspective on the foundational role of logic in programming and discuss the non-monotonic learning tasks that are intrinsically involved both at the general level of the development of a Cognitive Programming language and the specific level of the user's development of its own cognitive programs. These general concepts will be illustrated through a first example of a Cognitive Programming framework, called STAR, that is built by bringing together non-monotonic reasoning, reasoning about actions and belief revision within a logic based argumentation framework and adopting a cognitive perspective to logical inference. The talk will show how the STAR system is applied to the problem of automating the cognitive task of text (story) comprehension needed in the development of cognitive assistants.