No abstract

In this paper, we study the problem of answering questions of type "Could X cause Y?" where X and Y are general phrases without any constraints. Answering such questions will assist with various decision analysis tasks such as verifying and extending presumed causal associations used for decision making. Our goal is to analyze the ability of an AI agent built using state-of-the-art unsupervised methods in answering causal questions derived from collections of cause-effect pairs from human experts. We focus only on unsupervised and weakly supervised methods due to the difficulty of creating a large enough training set with a reasonable quality and coverage. The methods we examine rely on a large corpus of text derived from news articles, and include methods ranging from large-scale application of classic NLP techniques and statistical analysis to the use of neural network based phrase embeddings and state-of-the-art neural language models.

Abstract-Requirements can differ in their importance. As such the priorities that stakeholders associate with requirements may vary from stakeholder to stakeholder and from one situation to the next. Differing priorities, in turn, imply different design decisions for the end system. While elicitation of requirements priorities is a well studied activity, though, the modeling and reasoning side of prioritization has not enjoyed equal attention. In this paper, we address this by extending a traditional goal modeling notation to support the representation of optional and preference requirements. In our extension, optional goals are distinguished from mandatory ones. Then, quantitative prioritizations of the former are constructed and used as criteria for evaluating alternative ways to achieve the latter. A state-of-the-art preference-based planner is utilized to efficiently search for alternatives that best satisfy the given preferences. This way, analysts can acquire a better understanding of the impact of high-level stakeholder preferences to low-level design decisions.

Abstract. We claim that a key component of effective Web service composition, and one that has largely been ignored, is the consideration of user preferences. In this paper we propose a means of specifying and intergrating user preferences into Web service composition. To this end, we propose a means of performing automated Web service composition by exploiting generic procedures together with rich qualitative user preferences. We exploit the agent programming language Golog to represent our generic procedures and a first-order preference language to represent rich qualitative temporal user preferences. From these we generate Web service compositions that realize the generic procedure, satisfying the user's hard constraints and optimizing for the user's preferences. We prove our approach sound and optimal. Our system, GologPref, is implemented and interacting with services on the Web. The language and techniques proposed in this paper can be integrated into a variety of approaches to Web or Grid service composition.

We claim that user preferences are a key component of effective Web service composition, and one that has largely been ignored. In this paper we propose a means of specifying and intergrating user preferences into Web service composition. To this end, we propose a means of performing automated Web service composition by exploiting a flexible template of the composition in the form of a generic procedure. This template is augmented by a rich specification of user preferences that guide the instantiation of the template. We exploit the agent programming language Golog to represent our templates as Golog generic procedures and we exploit a first-order preference language to represent rich qualitative temporally-extended user preferences. From these we generate Web service compositions that realize a given generic procedure, satisfying the user's hard constraints and optimizing for the user's preferences. We prove our approach is sound and optimal. Our system, GologPref, is implemented and interacting with services on the Web. The language and techniques proposed in this paper can be integrated into a variety of approaches to Web or Grid service composition.