This study provided a content analysis of studies aiming to disclose how artificial intelligence has been applied to the education sector and explore the potential research trends and challenges of AI in education. A total of 100 papers including 63 empirical papers and 37 analytic papers were selected from the education and educational research category of Social Sciences Citation Index database from 2010 to 2020. The content analysis showed that the research questions could be classified into development layer, application layer, (...) and integration layer. Moreover, four research trends, including Internet of Things, swarm intelligence, deep learning, and neuroscience, as well as an assessment of AI in education, were suggested for further investigation. However, we also proposed the challenges in education may be caused by AI with regard to inappropriate use of AI techniques, changing roles of teachers and students, as well as social and ethical issues. The results provide insights into an overview of the AI used for education domain, which helps to strengthen the theoretical foundation of AI in education and provides a promising channel for educators and AI engineers to carry out further collaborative research. (shrink)

It was a common practice of the Chinese official historiographers to employ pseudo-historical, semi-fictional source materials alongside the factual, ascertainable data in their narratives for prescribed political or didactic purposes despite their commitment to the time-honored principles of truth and objectivity in the Confucian-oriented traditional historiography. The intrusion of these non-historical elements in the imperial historical records illustrates, therefore, the adaptability of the source materials representing the popular tradition of the masses for the uses of the great tradition, and the (...) propensity of the reciprocal exchanges between the expressions of the Confucian literati and the less cultured populace in historical compositions. Drawing on a textual analysis of the T'ai-tsu shih-lu, the reign chronicle of the Ming founder Chu Yüan-chang, who rose from a humble peasant to the imperial throne in 1368, this essay examines the historical circumstances and historiographical devices by which the factual records were commingled with the non-historical materials in the accounts of the dynasty founding. It shows how the historiographers synthesized the pseudo-historical expressions in the popular tradition with the deliberately fabricated falsehoods of their own doing to conjure up an inflated portrait of the Ming founder, transforming him from an illiterate, beggar mendicant monk and rebel leader into the topoi of a righteous hero, dynasty founder and exemplar ruler in traditional official historiography. It also shows that apart from the historiographers' penchant for conformity to the established conventions, the exaggerated portrait of the Ming founder in the T'ai-tsu shih-lu was a product of a historiographical revision undertaken on order of the third emperor Yung-lo, fourth son of T'ai-tsu, aiming at legitimizing his usurpation of the throne from his nephew the imperial successor Chien-wen in a palace rebellion of 1402. Lastly, it shows how the early Ming revision of the records of the rise of T'ai-tsu inspired a cycle of bizarre legends about the early years of the dynasty founding in later official and private writings, and how a case study of such historiographical process may add to our understanding of the continuous interactions between the expressions of the élite and mass heritages in the making of the Chinese intellectual and cultural traditions. (shrink)

On postmodernism; papers presented at a symposium organized by Tamil̲iyal Tur̲ai, Man̲ōn̲maṇiyam Cuntaran̲ār Palkalaikkal̲akam, Tirunelvēli.

For Viennese artist Florian Pumhösl »abstraction is a method«, not a category. Or rather, if abstraction is the defining category of modernism, the objective is to reproduce modernism's problems and limits and exploit relationships among its parts. Considering what Pumhösl calls the »textile complex« of modernism, this essay examines the artist's work in parallel with Charles Sanders Peirce's diagram concept and Gottfried Semper's use of textile diagrams throughout Style in the Technical and Tectonic Arts.

The year 2012 has witnessed worldwide celebrations of Alan Turing’s 100th birthday. A great number of conferences and workshops were organized by logicians, computer scientists and researchers in AI, showing the continued flourishing of computer science, and the fruitful interfaces between logic and computer science. Logic is no longer just the concept that Frege had about one hundred years ago, let alone that of Aristotle twenty centuries before. One of the prominent features of contemporary logic is its interdisciplinary character, connecting (...) across mathematics, philosophy, modern computer science, and even the cognitive and social sciences. -/- China is no exception. This special issue explores interfaces of logic with AI and other disciplines, and it attempts to give a bird’s eye view of the developing landscape of logic and AI in China. Our contributors come from computer science, AI, philosophy and linguistics, united by their interest in using formal logical tools and notions to deal with substantial problems in their fields. We are aware that AI is a vast area, and that the limitations of space in a volume like this may provide a somewhat incomplete or biased view. Still we hope that the six papers selected here illustrate the concerns and curiosity driving Chinese researchers, on topics shared with our colleagues around the world. -/- One of the active research areas in AI is planning under uncertainty, with incomplete knowledge, where a well-established logical framework is the action language of Son and Baral (Son and Baral 2001). This language can express the notions of sensing actions and making conditional plans. However, its current semantics is not yet satisfactory, since according to the semantics an agent would not have knowledge of what happens after a plan is executed, which can be a serious problem in a safety-critical environment. In their paper Proof Systems for Planning under Cautious Semantics (Shen and Zhao 2013), Yuping Shen and Xishun Zhao address this problem and propose a cautious and weakly cautious semantics for the action language. This new semantics enables the agent to know exactly what happens after executing an action. Hoare style proof systems are then proposed and proved to be sound and complete. What is more, the proposed new system reduces the reasoning complexity of the action language. -/- In Preferential Semantics for Plausible Subsumption in Possibility Theory (Qi and Zhang 2013), Guilin Qi and Zhizheng Zhang investigate another important issue in AI: how to handle exceptions in a knowledge-based system. This has become a hot topic in recent years, especially in ontological design, where description logics are widely used. The question then arises whether we can get a nonmonotonic extension of description logic. To answer this, the authors first propose three preferential semantics for plausible subsumption in the framework of possibility theory (Dubois and Prade 1985) and study their properties and their relationships. Then they introduce preferential subsumptions to a description logic-based knowledge system, and define an entailment relation of plausible subsumption. Moreover, they study reductions of the new semantics to standard semantics for an expressive description logic. -/- Counterfactual reasoning has been explored extensively by philosophers, cf. Lewis (1973), Stalnaker (1968). But in the last two decades, causal models have been proposed for modeling counterfactual reasoning by researchers in AI. In A Lewisian Logic of Causal Counterfactuals (Zhang 2013), Jiji Zhang studies classes of causal models and provides formal characterizations. In particular, a new logic system is proposed and proved complete for the class of ‘Lewisian models’ satisfying all the principles of David Lewis’s logic of counterfactuals. Moreover, Zhang compares his new framework with those of Lewis and Stalnaker, and also establishes formal connections with more recent approaches by Galles and Pearl, and by Halpern. -/- Consistency is a fundamental notion in logic, but it also plays a key role in many techniques for solving constraint satisfaction problems (Mackworth 1977). In Variable-Centered Consistency in Model RB (Li et al. 2013), Liang Li, Tian Liu and Ke Xu start with a discussion of i-consistency in ‘Model RB’ and ‘Model RD’, two models of random constraint satisfaction problems with growing domain size, then compare it with the notion of t-consistency and strong t-consistency in well-known earlier work by Freuder. After that, the authors define a new kind of variable-centered consistency, and show an upper bound on a suitably chosen parameter in Model RB and Model RD, such that up to this bound, all typical instances of Model RB are variable-centered consistent. -/- Language understanding is a cognitive process that human beings carry out every day. Metaphor is a pervasive phenomenon in natural languages, and its cognitive role calls for interpretation. There is a growing body of literature on cognitive mechanisms underlying metaphor. The paper An Ontology-Based Approach to Metaphor Cognitive Computation (Huang et al. 2013) by Xiaoxi Huang, Huaxin Huang, Beishui Liao, and Cihua Xu proposes a theoretical framework for metaphor understanding based on recent results from cognitive science (Shutova 2010). They then introduce ontology as a knowledge representation method, and present a new ontological model to formalize metaphor-based knowledge. An algorithmic description is provided using a quantitative measure of integrated degree, and its effectiveness is demonstrated. -/- Puzzles and their solution mechanisms are a recurrent theme in many fields. Dynamic epistemic logic (van Ditmarsch et al. 2007); (van Benthem 2011) is a recent framework that can handle information dynamics in knowledge puzzles. In Reasoning About Agent Types and the Hardest Logic Puzzle Ever (Liu and Wang 2013), Fenrong Liu and Yanjing Wang propose a new dynamic-epistemic logic that can specify different types of agents and analyse agents’ knowledge, communication and reasoning. To demonstrate its power, Smullyan’s well-known Knights and Knaves puzzles are formalized, as well as the Hardest Logic Puzzle Ever (HLPE) of Boolos (Boolos 1996). Moreover, a spectrum of new puzzles is found involving knowledge-based agent types, and their solution complexity is shown to be harder than that for existing logic puzzles. It is also shown that a version of HLPE in which the agents do not know the others’ types does not have a solution at all. -/- Finally, we would like to thank the editor of Minds and Machines, Gregory Wheeler, for his efficient assistance and kind support. We also thank Ties Nijssen at Springer for his encouragement to start this project at the first place. And of course, our appreciation goes to our authors, as well as all the colleagues who have helped us review the papers in this collection. (shrink)

Brief biography of Śaṅkarācārya, Hindu Advaita philosopher; includes his teachings.

Confucianism regarded mind-heart's nature with importance more than any other schools at all the time. Confucius was the first one to bring up the concept of mind-heart's nature in the history of chinese philosophy. Mencius was the first person to demonstrate reality of human nature's nature systematically and scientifically. Mencius was a protector to block heterodoxy after succeeding Confucius's the doctrine of mind-heart's nature. The mind-heart's nature provided by Mencius are 1) what distinguishes human beings from animals. 2) a moral (...) motivation of human beings. 3) comprised of benevolence(仁), righteousness(義), propriety(禮) and wisdom(智). T'oegye presented a The four & seven debate based Li-K with Gobong metaphysically. The four & seven debate was to present a moral motivation of human beings in their relation to metaphysical composition(Li-Ki). Li and Ki. human nature and particular with respect to metaphysical composition(Li-Ki). T'oegye introduced these of 'The four beginnings are the issuance of LI, and protected the human mind-heart's nature differed with other beings after succeeding Confucius-Mencius's the doctrine of mind-heart's nature. Such viewpoints about theory of mind-heart's nature plays an important role in the Age of AI. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Who Wrote This?: How AI and the Lure of Efficiency Threaten Human Writing by Naomi BaronLuke MunnBaron, Naomi. Who Wrote This?: How AI and the Lure of Efficiency Threaten Human Writing. Stanford University Press, 2023. 344pp.Who Wrote This? is Naomi Baron’s latest book exploring the emergence of AI language models and their potential implications for writing. A linguist, educator, and emeritus professor at American University, Baron should be (...) well placed to tease out the nuances of language, showcase the creativity of human literary canon across history, and deliver a set of findings and recommendations informed by deep experience. Indeed, since the release of ChatGPT in November 2022, there is a hunger for this kind of expertise and guidance both inside and outside academia, as the deluge of debates, panels, and forums in the past year have attested. This is the perfect storm, one that should be harnessed by a linguist with two decades of work on digital writing and reading into a powerful book. Instead, the reader must wade through a morass of truisms, historical anecdotes, and wiki-like summaries of research studies, interspersed with surface-level ponderings.The problems begin almost immediately with the structure of the book itself. While the book is ostensibly divided into chapters, each chapter is atomized into dozens of subsections, some no more than a paragraph or two in length. In this whirlwind tour, the reader is swiftly confronted with a jumble of quotes from journalists, jokes about language, historical events, a “laypersons AI roadmap,” and recent news stories, flitting from one to the next with barely a pause. The “AI Applications” section takes this same piecemeal approach, laying out the possible uses of artificial intelligence and then painstakingly stepping through each one. Each subsection features a few paragraphs that regurgitates material you might find, more cohesively and in-depth, in a Wikipedia article. The material on the history of artificial intelligence is handled simplistically and uncritically, skipping across a handful of heroic figures like Yann LeCun, Yoshua Bengio, and Fei-Fei Li.While anecdotes and quotes abound, an argument is much harder to locate. On the one hand, Baron seems to uncritically echo the AI hype that has dominated news headlines in the past year. “We’ve come a long way,” she opines, “we have vacuum cleaning robots, drones, and self-driving [End Page 156] cars” (59). The reader learns that AI can generate poetry, correct grammar, play games, and beat masters (AlphaGo), and even identify cancer (machine learning for mammograms). These use-cases, and the ambitious claims that accompany them, are never really challenged in any sustained theoretical or methodological way. On the other hand, Baron seems to be highly conservative when it comes to the proper domain of “the human” and of writing in particular. “AI isn’t up for self-expression or thinking” (14) she says in passing, dismissing the recent revolutionary improvements in large language models that she’s just hyped up.The possibility of machinic intelligence and creativity, in fact, is a fascinating if messy one. Turing was not so interested in demonstrably “proving” that computers could be intelligent, but instead (and very much in line with his everyday navigation of British sexual norms) in developing something that could “pass” as human. Intelligence was not an acid-test, but a set of gestures that could be performed or pantomimed, emulated until they were “good enough” to deceive. N. Katherine Hayles has continued this trajectory in her work on “non-conscious cognition,” removing the barriers to what qualifies as intelligence and subsequently extending cognition down to unicellular organisms and plants. Within my own work on language models alongside colleagues (Munn et al. 2023; Magee, Munn, and Arora 2023), we highlight how models like GPT 3.5 achieve an approximation of natural speech. What is important is not the authenticity or actual intelligence of this feat, but that this “good enough” ability means that users treat language models as an interlocutor, a listener, a subject. This projection, even if misplaced, opens up this interaction and requires a conceptualization that is at least as attuned to memory, affect, and subjectivity as software interfaces and linear... (shrink)