Foreground and background text in retrieval

Our hypothesis is that certain clauses have foreground functions in text, while other clauses have background functions and that these functions are expressed or reflected in the syntactic structure of the clause. Presumably these clauses will have differing utility for automatic approaches to text understanding; a summarization system might want to utilize background clauses to capture commonalities between numbers of documents while an indexing system might use foreground clauses in order to capture specific characteristics of a certain document

Proceedings of the 11th European Agent Systems Summer School Student Session

This volume contains the papers presented at the Student Session of the 11th European Agent Systems Summer School (EASSS) held on 2nd of September 2009 at Educatorio della Providenza, Turin, Italy. The Student Session, organised by students, is designed to encourage student interaction and feedback from the tutors. By providing the students with a conference-like setup, both in the presentation and in the review process, students have the opportunity to prepare their own submission, go through the selection process and present their work to each other and their interests to their fellow students as well as internationally leading experts in the agent field, both from the theoretical and the practical sector. Table of Contents: Andrew Koster, Jordi Sabater Mir and Marco Schorlemmer, Towards an inductive algorithm for learning trust alignment . . . 5; Angel Rolando Medellin, Katie Atkinson and Peter McBurney, A Preliminary Proposal for Model Checking Command Dialogues. . . 12; Declan Mungovan, Enda Howley and Jim Duggan, Norm Convergence in Populations of Dynamically Interacting Agents . . . 19; Akın Günay, Argumentation on Bayesian Networks for Distributed Decision Making . . 25; Michael Burkhardt, Marco Luetzenberger and Nils Masuch, Towards Toolipse 2: Tool Support for the JIAC V Agent Framework . . . 30; Joseph El Gemayel, The Tenacity of Social Actors . . . 33; Cristian Gratie, The Impact of Routing on Traffic Congestion . . . 36; Andrei-Horia Mogos and Monica Cristina Voinescu, A Rule-Based Psychologist Agent for Improving the Performances of a Sportsman . . . 39; --Autonomer Agent,Agent,Künstliche Intelligenz

Intonation and discourse : biased questions

This paper surveys a range of constructions in which prosody affects discourse function and discourse structure.We discuss English tag questions, negative polar questions, and what we call “focus” questions. We postulate that these question types are complex speech acts and outline an analysis in Segmented Discourse Representation Theory (SDRT) to account for the interactions between prosody and discourse

MaxSAT Evaluation 2022 : Solver and Benchmark Descriptions

Non peer reviewe

Designing Normative Theories for Ethical and Legal Reasoning: LogiKEy Framework, Methodology, and Tool Support

A framework and methodology---termed LogiKEy---for the design and engineering of ethical reasoners, normative theories and deontic logics is presented. The overall motivation is the development of suitable means for the control and governance of intelligent autonomous systems. LogiKEy's unifying formal framework is based on semantical embeddings of deontic logics, logic combinations and ethico-legal domain theories in expressive classic higher-order logic (HOL). This meta-logical approach enables the provision of powerful tool support in LogiKEy: off-the-shelf theorem provers and model finders for HOL are assisting the LogiKEy designer of ethical intelligent agents to flexibly experiment with underlying logics and their combinations, with ethico-legal domain theories, and with concrete examples---all at the same time. Continuous improvements of these off-the-shelf provers, without further ado, leverage the reasoning performance in LogiKEy. Case studies, in which the LogiKEy framework and methodology has been applied and tested, give evidence that HOL's undecidability often does not hinder efficient experimentation.Comment: 50 pages; 10 figure

Mapping the Relationships among the Cognitive Complexity of Independent Writing Tasks, L2 Writing Quality, and Complexity, Accuracy and Fluency of L2 Writing

Drawing upon the writing literature and the task-based language teaching literature, the study examined two cognitive complexity dimensions of L2 writing tasks: rhetorical task varying in reasoning demand and topic familiarity varying in the amount of direct knowledge of topics. Four rhetorical tasks were studied: narrative, expository, expo-argumentative, and argumentative tasks. Three topic familiarity tasks were investigated: personal-familiar, impersonal-familiar, and impersonal-less familiar tasks. Specifically, the study looked into the effects of these two cognitive complexity dimensions on L2 writing quality scores, their effects on complexity, accuracy, and fluency (CAF) of L2 production, and the predictive power of the CAF features on L2 writing scores for each task. Three hundred and seventy five Chinese university EFL students participated in the study, and each student wrote on one of the six writing tasks used to study the cognitive complexity dimensions. The essays were rated by trained raters using a holistic scale. Thirteen CAF measures were used, and the measures were all automated through computer tools. One-way ANOVA tests revealed that neither rhetorical task nor topic familiarity had an effect on the L2 writing scores. One-way MANOVA tests showed that neither rhetorical task nor topic familiarity had an effect on accuracy and fluency of the L2 writing, but that the argumentative essays were significantly more complex in global syntactic complexity features than the essays on the other rhetorical tasks, and the essays on the less familiar topic were significantly less complex in lexical features than the essays on the more familiar topics. All-possible subsets regression analyses revealed that the CAF features explained approximately half of the variance in the writing scores across the tasks and that writing fluency was the most important CAF predictor for five tasks. Lexical sophistication was however the most important CAF predictor for the argumentative task. The regression analyses further showed that the best regression models for the narrative task were distinct from the ones for the expository and argumentative types of tasks, and the best models for the personal-familiar task were distinct from the ones for the impersonal tasks