Proceedings of the First Workshop on Semantic Wikis – from Wiki to Semantics
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Why Machines Don't
KI - Künstliche Intelligenz https://doi.org/10.1007/s13218-019-00599-w SURVEY Why Machines Don’t (yet) Reason Like People Sangeet Khemlani1 · P. N. Johnson‑Laird2,3 Received: 15 February 2019 / Accepted: 19 June 2019 © This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2019 Abstract AI has never come to grips with how human beings reason in daily life. Many automated theorem-proving technologies exist, but they cannot serve as a foundation for automated reasoning systems. In this paper, we trace their limitations back to two historical developments in AI: the motivation to establish automated theorem-provers for systems of mathematical logic, and the formulation of nonmonotonic systems of reasoning. We then describe why human reasoning cannot be simulated by current machine reasoning or deep learning methodologies. People can generate inferences on their own instead of just evaluating them. They use strategies and fallible shortcuts when they reason. The discovery of an inconsistency does not result in an explosion of inferences—instead, it often prompts reasoners to abandon a premise. And the connectives they use in natural language have diferent meanings than those in classical logic. Only recently have cognitive scientists begun to implement automated reasoning systems that refect these human patterns of reasoning. A key constraint of these recent implementations is that they compute, not proofs or truth values, but possibilities. Keywords Reasoning · Mental models · Cognitive models 1 Introduction problems for mathematicians). Their other uses include the verifcation of computer programs and the design of com- The great commercial success of deep learning has pushed puter chips. -
Dialect Contact and Convergence in Contemporary Hutsulshchyna By
Coming Down From the Mountain: Dialect Contact and Convergence in Contemporary Hutsulshchyna By Erin Victoria Coyne A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Slavic Languages and Literatures in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Johanna Nichols, Chair Professor Alan Timberlake Professor Lev Michael Spring 2014 Abstract Coming Down From the Mountain: Dialect Contact and Convergence in Contemporary Hutsulshchyna by Erin Victoria Coyne Doctor of Philosophy in Slavic Languages and Literatures University of California, Berkeley Professor Johanna Nichols, Chair Despite the recent increased interest in Hutsul life and culture, little attention has been paid to the role of dialect in Hutsul identity and cultural revival. The primary focus of the present dissertation is the current state of the Hutsul dialect, both in terms of social perception and the structural changes resulting from the dominance of the standard language in media and education. Currently very little is known about the contemporary grammatical structure of Hutsul. The present dissertation is the first long-term research project designed to define both key elements of synchronic Hutsul grammar, as well as diachronic change, with focus on variation and convergence in an environment of increasing close sustained contact with standard Ukrainian resulting from both a historically-based sense of ethnic identification, as well as modern economic realities facing the once isolated and self-sufficient Hutsuls. In addition, I will examine the sociolinguistic network lines which allow and impede linguistic assimilation, specifically in the situation of a minority population of high cultural valuation facing external linguistic assimilation pressures stemming from socio-political expediency. -
Towards the Implementation of an Intelligent Software Agent for the Elderly Amir Hossein Faghih Dinevari
Towards the Implementation of an Intelligent Software Agent for the Elderly by Amir Hossein Faghih Dinevari A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science Department of Computing Science University of Alberta c Amir Hossein Faghih Dinevari, 2017 Abstract With the growing population of the elderly and the decline of population growth rate, developed countries are facing problems in taking care of their elderly. One of the issues that is becoming more severe is the issue of compan- ionship for the aged people, particularly those who chose to live independently. In order to assist the elderly, we suggest the idea of a software conversational intelligent agent as a companion and assistant. In this work, we look into the different components that are necessary for creating a personal conversational agent. We have a preliminary implementa- tion of each component. Among them, we have a personalized knowledge base which is populated by the extracted information from the conversations be- tween the user and the agent. We believe that having a personalized knowledge base helps the agent in having better, more fluent and contextual conversa- tions. We created a prototype system and conducted a preliminary evaluation to assess by users conversations of an agent with and without a personalized knowledge base. ii Table of Contents 1 Introduction 1 1.1 Motivation . 1 1.1.1 Population Trends . 1 1.1.2 Living Options for the Elderly . 2 1.1.3 Companionship . 3 1.1.4 Current Technologies . 4 1.2 Proposed System . 5 1.2.1 Personal Assistant Functionalities . -
An Overview of Automated Reasoning
An overview of automated reasoning John Harrison Intel Corporation 3rd February 2014 (10:30{11:30) Talk overview I What is automated reasoning? I Early history and taxonomy I Automation, its scope and limits I Interactive theorem proving I Hobbes (1651): \Reason . is nothing but reckoning (that is, adding and subtracting) of the consequences of general names agreed upon, for the marking and signifying of our thoughts." I Leibniz (1685) \When there are disputes among persons, we can simply say: Let us calculate [calculemus], without further ado, to see who is right." Nowadays, by `automatic and algorithmic' we mean `using a computer program'. What is automated reasoning? Attempting to perform logical reasoning in an automatic and algorithmic way. An old dream! I Leibniz (1685) \When there are disputes among persons, we can simply say: Let us calculate [calculemus], without further ado, to see who is right." Nowadays, by `automatic and algorithmic' we mean `using a computer program'. What is automated reasoning? Attempting to perform logical reasoning in an automatic and algorithmic way. An old dream! I Hobbes (1651): \Reason . is nothing but reckoning (that is, adding and subtracting) of the consequences of general names agreed upon, for the marking and signifying of our thoughts." Nowadays, by `automatic and algorithmic' we mean `using a computer program'. What is automated reasoning? Attempting to perform logical reasoning in an automatic and algorithmic way. An old dream! I Hobbes (1651): \Reason . is nothing but reckoning (that is, adding and subtracting) of the consequences of general names agreed upon, for the marking and signifying of our thoughts." I Leibniz (1685) \When there are disputes among persons, we can simply say: Let us calculate [calculemus], without further ado, to see who is right." What is automated reasoning? Attempting to perform logical reasoning in an automatic and algorithmic way. -
Personal Knowledge Base Construction from Text-Based Lifelogs
Session 2C: Knowledge and Entities SIGIR ’19, July 21–25, 2019, Paris, France Personal Knowledge Base Construction from Text-based Lifelogs An-Zi Yen1, Hen-Hsen Huang23, Hsin-Hsi Chen13 1Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan 2Department of Computer Science, National Chengchi University, Taipei, Taiwan 3MOST Joint Research Center for AI Technology and All Vista Healthcare, Taiwan [email protected], [email protected], [email protected] ABSTRACT Previous work on lifelogging focuses on life event extraction from 1. INTRODUCTION image, audio, and video data via wearable sensors. In contrast to Life event extraction from social media data provides wearing an extra camera to record daily life, people are used to complementary information for individuals. For example, in the log their life on social media platforms. In this paper, we aim to tweet (T1), there is a life event of the user who reads the book extract life events from textual data shared on Twitter and entitled “Miracles of the Namiya General Store” and enjoys it. The construct personal knowledge bases of individuals. The issues to enriched repository personal information is useful for memory be tackled include (1) not all text descriptions are related to life recall and supports living assistance. events, (2) life events in a text description can be expressed explicitly or implicitly, (3) the predicates in the implicit events are (T1) 東野圭吾的《解憂雜貨店》真好看 (Higashino Keigo's often absent, and (4) the mapping from natural language “Miracles of the Namiya General Store” is really nice.) predicates to knowledge base relations may be ambiguous. -
Automated Reasoning for Explainable Artificial Intelligence∗
EPiC Series in Computing Volume 51, 2017, Pages 24–28 ARCADE 2017. 1st International Workshop on Automated Reasoning: Challenges, Appli- cations, Directions, Exemplary Achievements Automated Reasoning for Explainable Artificial Intelligence∗ Maria Paola Bonacina1 Dipartimento di Informatica Universit`adegli Studi di Verona Strada Le Grazie 15 I-37134 Verona, Italy, EU [email protected] Abstract Reasoning and learning have been considered fundamental features of intelligence ever since the dawn of the field of artificial intelligence, leading to the development of the research areas of automated reasoning and machine learning. This paper discusses the relationship between automated reasoning and machine learning, and more generally be- tween automated reasoning and artificial intelligence. We suggest that the emergence of the new paradigm of XAI, that stands for eXplainable Artificial Intelligence, is an oppor- tunity for rethinking these relationships, and that XAI may offer a grand challenge for future research on automated reasoning. 1 Artificial Intelligence, Automated Reasoning, and Ma- chine Learning Ever since the beginning of artificial intelligence, scientists concurred that the capability to learn and the capability to reason about problems and solve them are fundamental pillars of intelligent behavior. Similar to many subfields of artificial intelligence, automated reasoning and machine learning have grown into highly specialized research areas. Both have experienced the dichotomy between the ideal of imitating human intelligence, whereby the threshold of success would be the indistinguishability of human and machine, as in the Turing’s test [12], and the ideal that machines can and should learn and reason in their own way. According to the latter ideal, the measure of success is independent of similarity to human behavior. -
Document Structure Aware Relational Graph Convolutional Networks for Ontology Population
Document Structure aware Relational Graph Convolutional Networks for Ontology Population Abhay M Shalghar1?, Ayush Kumar1?, Balaji Ganesan2, Aswin Kannan2, and Shobha G1 1 RV College of Engineering, Bengaluru, India fabhayms.cs18,ayushkumar.cs18,[email protected] 2 IBM Research, Bengaluru, India fbganesa1,[email protected] Abstract. Ontologies comprising of concepts, their attributes, and re- lationships, form the quintessential backbone of many knowledge based AI systems. These systems manifest in the form of question-answering or dialogue in number of business analytics and master data manage- ment applications. While there have been efforts towards populating do- main specific ontologies, we examine the role of document structure in learning ontological relationships between concepts in any document cor- pus. Inspired by ideas from hypernym discovery and explainability, our method performs about 15 points more accurate than a stand-alone R- GCN model for this task. Keywords: Graph Neural Networks · Information Retrieval · Ontology Population 1 Introduction Ontology induction (creating an ontology) and ontology population (populating ontology with instances of concepts and relations) are important tasks in knowl- edge based AI systems. While the focus in recent years has shifted towards au- tomatic knowledge base population and individual tasks like entity recognition, entity classification, relation extraction among other things, there are infrequent advances in ontology related tasks. Ontologies are usually created manually and tend to be domain specific i.e. arXiv:2104.12950v1 [cs.AI] 27 Apr 2021 meant for a particular industry. For example, there are large standard ontologies like Snomed for healthcare, and FIBO for finance. However there are also require- ments that are common across different industries like data protection, privacy and AI fairness. -
Journal of Ukrainian Studies 21
JOURNAL OF UKRAINIAN STUDIES Oleh W. Gerus: Ukrainians in Argentina: A Canadian Perspective Serge Cipko: The Legacy of the “Brazilian Fever”: The Ukrainian Colonization of Parana Eugene Seneta: On the Number of Ukrainians in Australia in 1979 Serge Cipko and Oleh Leszczyszyn: Survey of Second-Generation Ukrainians in Britain Bohdan Struminsky: Linguistics in Ukraine, 1980-85 MHKOJia MyiuHHKa: ManoninoMa ctutth npo nonaTKH yKpaiHCBKHx mKiji y Kanani Lubomyr Y. Luciuk: An Annotated Guide to Certain Microfiched Archives of the Association of Ukrainians in Great Britain Book Reviews 21 WINTER1986 )ICyPHAA YKPAIH03HABMMX CTXAm EDITOR Myroslav Yurkevich EDITORIAL BOARD John-Paul Himka, University of Alberta • Andrij Hornjatkevyc, University of Alberta • Oleh Ilnytzkyj, University of Alberta • Bohdan Kordan, Arizona State University • Bohdan Krawchenko, University of Alberta • Manoly R. Lupul, University of Alberta • David Marples, University of Alberta • Bohdan Medwidsky, University of Alberta • Natalia Pylypiuk, Harvard University • Peter A. Rolland, University of Alberta • Frances A. Swyripa, University of Alberta The Journal of Ukrainian Studies is published semiannually, in the summer and winter, by the Canadian Institute of Ukrainian Studies. Annual subscription rates are $10.00 for individuals and $15.00 for libraries and institutions. Cheques and money orders are payable in Canadian or American funds only to Journal of Ukrainian Studies. Please do not send cash. Subscribers outside Canada: please pay in U.S. funds. The Journal publishes articles on Ukrainian-related subjects in the humanities and social sciences. The criterion for acceptance of submissions is their scholarly contribution to the field of Ukrainian studies. The Journal also publishes translations, documents, information, book reviews, letters, and journalistic articles of a problem-oriented, controversial nature. -
The Ratiolog Project: Rational Extensions of Logical Reasoning
The RatioLog Project: Rational Extensions of Logical Reasoning Ulrich Furbach · Claudia Schon · Frieder Stolzenburg · Karl-Heinz Weis · Claus-Peter Wirth Abstract Higher-level cognition includes logical reasoning 1 Rational Reasoning and Question Answering and the ability of question answering with common sense. The RatioLog project addresses the problem of rational rea- The development of formal logic played a big role in the soning in deep question answering by methods from auto- field of automated reasoning, which led to the development mated deduction and cognitive computing. In a first phase, of the field of artificial intelligence (AI). Applications of au- we combine techniques from information retrieval and ma- tomated deduction in mathematics have been investigated chine learning to find appropriate answer candidates from from the early years on. Nowadays automated deduction the huge amount of text in the German version of the free techniques are successfully applied in hard- and software encyclopedia “Wikipedia”. In a second phase, an automated verification and many other areas (for an overview see [2]). theorem prover tries to verify the answer candidates on In contrast to formal logical reasoning, however, human the basis of their logical representations. In a third phase reasoning does not strictly follow the rules of classical logic. — because the knowledge may be incomplete and inconsis- Reasons may be incomplete knowledge, incorrect beliefs, tent —, we consider extensions of logical reasoning to im- and inconsistent norms. From the very beginning of AI re- prove the results. In this context, we work toward the appli- search, there has been a strong emphasis on incorporating cation of techniques from human reasoning: We employ de- mechanisms for rationality, such as abductive or defeasible feasible reasoning to compare the answers w.r.t. -
Automated Reasoning on the Web
Automated Reasoning on the Web Slim Abdennadher1, Jos´eJ´ulioAlves Alferes2, Grigoris Antoniou3, Uwe Aßmann4, Rolf Backofen5, Cristina Baroglio6, Piero A. Bonatti7, Fran¸coisBry8, W lodzimierz Drabent9, Norbert Eisinger8, Norbert E. Fuchs10, Tim Geisler11, Nicola Henze12, Jan Ma luszy´nski4, Massimo Marchiori13, Alberto Martelli14, Sara Carro Mart´ınez15, Wolfgang May16, Hans J¨urgenOhlbach8, Sebastian Schaffert8, Michael Schr¨oder17, Klaus U. Schulz8, Uta Schwertel8, and Gerd Wagner18 1 German University in Cairo (Egypt), 2 New University of Lisbon (Portugal), 3 Institute of Computer Science, Foundation for Research and Technology – Hel- las (Greece), 4 University of Link¨oping (Sweden), 5 University of Jena (Germany), 6 University of Turin (Italy), 7 University of Naples (Italy), 8 University of Mu- nich (Germany), 9 Polish Academy of Sciences (Poland), 10 University of Zurich (Switzerland), 11 webXcerpt (Germany), 12 University of Hannover (Germany), 13 University of Venice (Italy), 14 University of Turin (Italy), 15 Telef´onica Investi- gaci´ony Desarollo (Spain), 16 University of G¨ottingen(Germany), 17 University of Dresden (Germany), 18 University of Eindhoven (The Netherlands) Abstract Automated reasoning is becoming an essential issue in many Web systems and applications, especially in emerging Semantic Web applications. This article first discusses reasons for this evolution. Then, it presents research issues currently investigated towards automated reasoning on the Web and it introduces into selected applications demonstrating the practical impact of the approach. Finally, it introduces a research endeavor called REWERSE (cf. http://rewerse.net) recently launched by the authors of this article which is concerned with developing automated reasoning methods and tools for the Web as well as demonstrator applications. -
Scandinavian Influence in Kievan Rus
Katie Lane HST 499 Spring 2005 VIKINGS IN THE EAST: SCANDINAVIAN INFLUENCE IN KIEVAN RUS The Vikings, referred to as Varangians in Eastern Europe, were known throughout Europe as traders and raiders, and perhaps the creators or instigators of the first organized Russian state: Kievan Rus. It is the intention of this paper to explore the evidence of the Viking or Varangian presence in Kievan Rus, more specifically the areas that are now the Ukraine and Western Russia. There is not an argument over whether the Vikings were present in the region, but rather over the effect their presence had on the native Slavic people and their government. This paper will explore and explain the research of several scholars, who generally ascribe to one of the rival Norman and Anti- Norman Theories, as well as looking at the evidence that appears in the Russian Primary Chronicle, some of the laws in place in the eleventh century, and two of the Icelandic Sagas that take place in modern Russia. The state of Kievan Rus was the dominant political entity in the modern country the Ukraine and western Russia beginning in the tenth century and lasting until Ivan IV's death in 1584.1 The region "extended from Novgorod on the Volkhov River southward across the divide where the Volga, the West Dvina, and the Dnieper Rivers all had their origins, and down the Dnieper just past Kiev."2 It was during this period that the Slavs of the region converted to Christianity, under the ruler Vladimir in 988 C.E.3 The princes that ruled Kievan Rus collected tribute from the Slavic people in the form of local products, which were then traded in the foreign markets, as Janet Martin explains: "The Lane/ 2 fur, wax, and honey that the princes collected from the Slav tribes had limited domestic use. -
Knowledge Management in the Learning Society
THE PRODUCTION, MEDIATION AND USE OF PROFESSIONAL KNOWLEDGE AMONG TEACHERS AND DOCTORS: A COMPARATIVE ANALYSIS by David H. Hargreaves School of Education, University of Cambridge, United Kingdom The most pressing need confronting the study of professions is for an adequate method of conceptualizing knowledge itself. Eliot Freidson, 1994 Introduction The are two grounds for undertaking a comparative analysis of the knowledge-base and associated processes of the medical and teaching professions. First, by examining the similarities and differences between the two professions, it should be possible to advance a generic model of a professional knowl- edge-base. Secondly, the contrast offers some indications of what each profession might learn from the other. In this chapter, doctors and teachers are compared in relation to their highly contrasting knowledge- bases. Whereas the knowledge-base of doctors is rooted in the biomedical sciences, teachers have no obvious equivalent, and the attempt to find one in the social sciences has so far largely failed. Yet both professions share a central core to their knowledge-base, namely the need to generate systems for clas- sifying the diagnoses of their clients’ problems and possible solutions to them. Contrasts are drawn between the styles of training for doctors and teachers, with doctors having retained some strengths from an apprenticeship model and teachers now developing more sophisticated systems for mentoring train- ees. In both professions, practice is often less grounded in evidence about effectiveness than is com- monly believed, but practitioner-led research and evidence-based medicine have put doctors far in advance of teachers. Adaptations of some developments in medicine could be used to improve the sys- temic capacities for producing and disseminating the knowledge which is needed for a better profes- sional knowledge-base for teachers.