Let's plan it deductively!

AbstractThe paper describes a transition logic, TL, and a deductive formalism for it. It shows how various important aspects (such as ramification, qualification, specificity, simultaneity, indeterminism etc.) involved in planning (or in reasoning about action and causality for that matter) can be modelled in TL in a rather natural way. (The deductive formalism for) TL extends the linear connection method proposed earlier by the author by embedding the latter into classical logic, so that classical and resource-sensitive reasoning coexist within TL. The attraction of a logical and deductive approach to planning is emphasized and the state of automated deduction briefly described

Cognitive Modeling for Computer Animation: A Comparative Review

Cognitive modeling is a provocative new paradigm that paves the way towards intelligent graphical characters by providing them with logic and reasoning skills. Cognitively empowered self-animating characters will see in the near future a widespread use in the interactive game, multimedia, virtual reality and production animation industries. This review covers three recently-published papers from the field of cognitive modeling for computer animation. The approaches and techniques employed are very different. The cognition model in the first paper is built on top of Soar, which is intended as a general cognitive architecture for developing systems that exhibit intelligent behaviors. The second paper uses an active plan tree and a plan library to achieve the fast and robust reactivity to the environment changes. The third paper, based on an AI formalism known as the situation calculus, develops a cognitive modeling language called CML and uses it to specify a behavior outline or sketch plan to direct the characters in terms of goals. Instead of presenting each paper in isolation then comparatively analyzing them, we take a top-down approach by first classifying the field into three different categories and then attempting to put each paper into a proper category. Hopefully in this way it can provide a more cohesive, systematic view of cognitive modeling approaches employed in computer animation

Between the crises: migration politics and the three periods of neoliberalism

Between the two UK referendums on European Community/European Union membership, the issue of migration came to dominate the entire debate. The period between 1975 and 2016 corresponds almost exactly to the neoliberal era in capitalism, in its British manifestation, and this is not coincidental. This article traces the shifting periods of neoliberalism (‘vanguard’, ‘social’ and ‘crisis’) across these 40 years, focusing in each case on how the policies associated with them specifically impacted migration into the United Kingdom. In particular, it will argue that the current migration crisis is at least partly an aspect of the wider crisis of neoliberalism as a form of capitalist organisation. It concludes that current levels of anti-migrant sentiment are a displaced expression of hostility to the social effects of neoliberalism, and which may nevertheless cause difficulties for British capital through the imposition of anti-free movement policies to which it is opposed

Sociocognition Issues Affecting the Working Relationship between the Deaf Professional and the Interpreter

The focus of this paper is to review the literature on socio-cognition issues for deaf graduate students and professionals working with interpreters in order to assess its usefulness in developing key conditions under which deaf graduate student/professional- interpreterworkingrelationshipsmightbeimplementedmoreeffectively. Theories on cognitive dissonance and stereotyping will be examined in relation to their possible implications in the working relationship, and included in this review if they related to the development and maintenance of an ongoing working relationship between the deaf professional and the interpreter. The concept, cognitive dissonance, will be introduced in this discussion and examined for its relevance to the inconsistency between attitudes and behaviors that emerge in the deaf professional or the interpreter as they enter the working relationship. This paper may provide insights into the mechanisms of developing an ongoing working relationship which may guide development of advanced or specialized interpreter training programs

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

Improving English Language Skills and Methods through Short Term Trainings: Bridging High School and University Teachers

The purpose of this article was to show how universities can make interventions in improving the classroom practices of high schools and preparatory schools English language teachers. The data gathering instrument was questionnaire and interview from secondary and preparatory school teachers of Tabor cluster that include Tabor Secondary and Preparatory school, Alamura High School Gemeto-Gale Secondary School, and Tula Secondary and Preparatory school and two school principals. The teachers received short term English language trainings from university teachers. It was, therefore, reflections of the teachers on improvements the training brought on their teaching skills on one hand and their attitudes on “the-to-be” links between the university instructors and high school teachers on the other hand. The link and the interventions envisaged to bring continuous improvements in the English language skills of secondary school English language teachers and thereby the skills of their students who ultimately and continuously join universities. As the study was based on the teachers and the principals who took part in the training, the sample size considered was the whole population, 40. Since the data was obtained qualitatively through interview and quantitatively through questionnaire, the analysis method also followed mixed methods. The quantitative data was analyzed descriptively with SPSS version 20, and the data obtained through interview was grouped into themes with open-code 3.6 and then described textually. The study showed that the short term trainings, which were based on the trainees’ pre-identified areas of English language skill gaps, helped to alleviate the gaps of the teachers to a greater extent. It also showed that there are other areas of English language skill gaps that need further trainings. Regarding the teachers’ attitude on the high schools and University teachers’ professional link, it was found out that high school teachers need supports from universities to improve their own and their students’ English language skills. It was also discovered that the link among school and university teachers so far is very weak. The trainees suggested areas of their special concerns to improve their English language skills, and areas university teachers may benefit from high schools

Learning non-monotonic Logic Programs to Reason about Actions and Change

[Resumen] El objetivo de esta tesis es el diseño de métodos de aprendizaje automático capaces de encontrar un modelo de un sistema dinámico que determina cómo las propiedades del sistema con afectadas por la ejecución de acciones, Esto permite obtener de manera automática el conocimiento específico del dominio necesario para las tareas de planficación o diagnóstico así como predecir el comportamiento futuro del sistema. La aproximación seguida difiere de las aproximaciones previas en dos aspectos. Primero, el uso de formalismos no monótonos para el razonamiento sobre acciones y el cambio con respecto a los clásicos operadores tipo STRIPS o aquellos basados en formalismos especializados en tareas muy concretas, y por otro lado el uso de métodos de aprendizaje de programas lógicos (Inductive Logic Programming). La combinación de estos dos campos permite obtener un marco declarativo para el aprendizaje, donde la especificación de las acciones y sus efectos es muy intuitiva y natural y que permite aprender teorías más expresivas que en anteriores aproximaciones