Towards Practical Argumentation-Based Dialogues in Multi-agent Systems

Hazardous waste capacity assurance planning: Volumes for one‐time remediation

The research aimed to identify the reality of using artificial intelligence in educational research from the point of view of graduate students at the College of Education at Taif University. The study sample consisted of 32.8% of the study population consisting of (128 male and female students) enrolled in the master’s degree- at the College of Education- Taif University In the specializations of (educational leadership, pedagogy, educational policies, special education, curricula, teaching methods and educational techniques) in the second semester of the academic year 1444-1445 AH, and using the questionnaire tool, the research concluded the following: 1- That students use artificial intelligence to a high degree in all stages of research. 2- One of the most important problems in using artificial intelligence in research is related to reliability and security, and the lack of a clear policy for applying artificial intelligence in educational research. 3- One of the most important controls that students believed should be available (formulation The Artificial Intelligence Ethics Document, the establishment of the University Center for Artificial Intelligence Ethics, and the enhancement of cyber security skills for the educational researcher, while there are no statistically significant differences between the sample members in their responses to the questionnaire axes due to specialization and level While the most widely used artificial intelligence program in educational research was Chat GPT, it affected the reality axis without the rest of the axes. Among the most important recommendations reached by this study: establishing a university center for the ethics of artificial intelligence, drafting a document on the ethics of artificial intelligence in educational research, and adding it as a course for students. Undergraduate and postgraduate studies

This letter highlights the necessity of nursing engagement in artificial intelligence (AI) research and its potential impact on healthcare. As AI transforms patient care, diagnostics, and operational efficiency, it is crucial for nurses, the largest healthcare workforce, to engage in AI development actively. Nurses’ experiential knowledge and ethical perspectives can enhance AI tools, ensuring they are patient-centered and practically applicable. This letter underscores the importance of interdisciplinary collaboration and advocates for increased nursing involvement in AI research to achieve better healthcare outcomes.

Countries, companies, and universities are increasingly competing over top-tier artificial intelligence (AI) researchers. Where are these researchers likely to immigrate and what affects their immigration decisions? We conducted a survey $(n = 524)$ of the immigration preferences and motivations of researchers that had papers accepted at one of two prestigious AI conferences: the Conference on Neural Information Processing Systems (NeurIPS) and the International Conference on Machine Learning (ICML). We find that the U.S. is the most popular destination for AI researchers, followed by the U.K., Canada, Switzerland, and France. A country's professional opportunities stood out as the most common factor that influences immigration decisions of AI researchers, followed by lifestyle and culture, the political climate, and personal relations. The destination country's immigration policies were important to just under half of the researchers surveyed, while around a quarter noted current immigration difficulties to be a deciding factor. Visa and immigration difficulties were perceived to be a particular impediment to conducting AI research in the U.S., the U.K., and Canada. Implications of the findings for the future of AI talent policies and governance are discussed.

Transparency in Artificial Intelligence Research: a Systematic Review of Availability Items Related to Open Science in Radiology and Nuclear Medicine

A brief summary of a lengthy work of writing, such as a book, research paper, or thesis, is called an abstract. It describes the key concepts, methods, findings, and conclusions, and is usually positioned at the beginning of the document. start of academic or professional documents, abstracts help an abstract serve as a tool that allows readers can rapidly comprehend a work’s primary goal and focus without the requirement for to read the entire document. It enables readers to effectively understand the content’s goals and relevance. is to provide a preview of the information, helping readers decide whether the full document is relevant to their research or interests. It summarizes the main problem or question addressed, the methods or approach used to investigate it, and the significant outcomes or conclusions drawn. It typically contains a brief introduction, methodology, results. Abstracts are commonly used in academic journals, conferences, and other scholarly publications, as well as in research proposals and grant applications. A range of technologies collectively referred to as artificial intelligence (AI) enable computers to do complex tasks, such as data analysis, spoken or written language comprehension and translation, visual perception, and more. making suggestions. A well-written abstract can improve the visibility and accessibility of a work, as it allows researchers and professionals to quickly assess its relevance. Clear, concise, and accurate representation of the core ideas is essential for a successful abstract. Research significance: Artificial intelligence (AI) research is transformative, driving advancements in technology, society, and the economy. It fosters innovation in areas like automation, robotics, and data analysis, enabling more efficient systems and unlocking new possibilities. In healthcare, AI enhances diagnostics, personalizes treatments, and accelerates drug discovery, while in education, it provides adaptive learning tailored to individual needs. Economically, AI boosts productivity, creates new markets, and improves decision-making through data-driven insights. It also discusses global concerns including food security, public health, and climate change. can be addressed by enhancing and streamlining solutions and predictive modeling. AI research raises important ethical and philosophical questions, ensuring fairness, transparency, and responsible use. Additionally, it strengthens national and global security through advancements in defense and cybersecurity. Beyond practical applications, AI deepens our understanding of cognition and expands exploration into uncharted territories. AI research is a cornerstone of progress, reshaping society and empowering humanity to address the future. Methodology: The Demetal Methodology It is a structured method employed to study and represent intricate systems. by examining interrelationships among various factors. It combines qualitative and quantitative techniques to identify cause-effect relationships, prioritize issues, and facilitate decision-making. This methodology is particularly effective in fields like systems engineering, supply chain management, and social sciences, where interdependencies play a significant role. It begins with identifying key factors or components of a system, followed by expert input to establish connections and weightages between them. Using tools like pairwise comparison matrices, it quantifies these relationships, enabling visualization through causal diagrams or directed graphs. Alternative: Water quality, spa amenities, affordability, ease of access, and reputation. Evalution parameter: Water Quality, SPA Facilities, Cost, Accessibility, Reputation. Result: Water Quality (1): The first rank which may imply that basic standards are assumed or that it is less influential in decision-making compared to other factors. SPA Facilities (5): The last rank, emphasizing the importance of high-quality amenities and treatment options for a superior customer experience.

This interdisciplinary volume introduces new theories and ideas on creativity from the perspectives of science and art. Featuring contributions from leading researchers, theorists and artists working in artificial intelligence, generative art, creative computing, music composition, and cybernetics, the book examines the relationship between computation and creativity from both analytic and practical perspectives. Each contributor describes innovative new ways creativity can be understood through, and inspired by, computers. The book tackles critical philosophical questions and discusses the major issues raised by computational creativity, including: whether a computer can exhibit creativity independently of its creator; what kinds of creativity are possible in light of our knowledge from computational simulation, artificial intelligence, evolutionary theory and information theory; and whether we can begin to automate the evaluation of aesthetics and creativity in silico. These important, often controversial questions are contextualised by current thinking in computational creative arts practice. Leading artistic practitioners discuss their approaches to working creatively with computational systems in a diverse array of media, including music, sound art, visual art, and interactivity. The volume also includes a comprehensive review of computational aesthetic evaluation and judgement research, alongside discussion and insights from pioneering artists working with computation as a creative medium over the last fifty years. A distinguishing feature of this volume is that it explains and grounds new theoretical ideas on creativity through practical applications and creative practice. Computers and Creativity will appeal to theorists, researchers in artificial intelligence, generative and evolutionary computing, practicing artists and musicians, students and any reader generally interested in understanding how computers can impact upon creativity. It bridges concepts from computer science, psychology, neuroscience, visual art, music and philosophy in an accessible way, illustrating how computers are fundamentally changing what we can imagine and create, and how we might shape the creativity of the future. Computers and Creativity will appeal to theorists, researchers in artificial intelligence, generative and evolutionary computing, practicing artists and musicians, students and any reader generally interested in understanding how computers can impact upon creativity. It bridges concepts from computer science, psychology, neuroscience, visual art, music and philosophy in an accessible way, illustrating how computers are fundamentally changing what we can imagine and create, and how we might shape the creativity of the future.

It is the contention of this paper that ethics of work ought to be anthropological, and artificial intelligence (AI) research and development, which is the focus of work today, should be anthropological, that is, human-centered. This paper discusses the philosophical and theological implications of the development of AI research on the intrinsic nature of work and the nature of the human person. AI research and the implications of its development and advancement, being a relatively new phenomenon, have not been comprehensively interrogated in the social and ethical teachings of the Catholic Church. This paper, therefore, proposes a path for this interrogation by expounding a discourse which is believed to be epistemically helpful in the developing discourse of AI in the ethical and social teachings of the Church. The advancement in the research on AI is not only redefining the meaning of work, but, even more so, it is questioning the metaphysical notion of the human person and the theological notion of work as an intrinsic part in the selfhood and dignity of the human person.

Meta-learning, social cognition and consciousness in brains and machines

Since the early 1970s, researchers in artificial intelligence (AI) have investigated a class of combinatorial problems that became known as constraint-satisfaction problems (CSP). The input to such a problem consists of a set of variables, a set of possible values for the variables, and a set of constraints between the variables; the question is to determine whether there is an assignment of values to the variables that satisfies the given constraints. The study of constraint satisfaction occupies a prominent place in artificial intelligence, because many problems that arise in different areas can be modelled as constraint-satisfaction problems in a natural way; these areas include Boolean satisfiability, temporal reasoning, belief maintenance, machine vision, and scheduling (cf. [Dec92a,Kum92,Mes89, Tsa93]). In its full generality, constraint satisfaction is an NP-complete problem. For this reason, researchers in artificial intelligence have pursued both heuristics for constraint-satisfaction problems and tractable cases obtained by imposing various restrictions on the input (cf. [MF93,Dec92a,DM94,Fro97,PJ97]).

<p indent="0mm">The development of sexual reproductive organism embryos begins with the fertilization process, where sperm and egg unite, followed by a series of intricate and orchestrated changes, leading to continuous embryo development and tissue differentiation, culminating in the formation of a complete biological individual. Conducting in-depth and systematic exploration of this intricate and complex process represents a monumental and challenging undertaking. Artificial intelligence, is aimed at emulating the human brain and assisting in addressing more complex problems. With the continuous updating of computing devices and the successive ascent of computing capabilities, artificial intelligence has experienced rapid development, achieving groundbreaking advancements in various fields. In the field of life sciences, artificial intelligence has a wide range of applications, especially in the study of gamete and embryo development, where it was applied in the relatively early days. From gamete selection to embryo quality assessment, and from investigating molecular mechanisms underlying embryo development to elucidating the interconnectedness among various modules during embryo development, including time, phenotype, and molecular features, artificial intelligence has been effectively utilized, demonstrating significant advantages. Hence, exploring how to better leverage artificial intelligence in the research process of gamete and embryo development is a question worthy of deeper investigation at this stage. This paper provides a comprehensive review of the current applications of artificial intelligence in gamete and embryo development research, along with an analysis of the challenges and directions for its future development.

If you are an artificial intelligence researcher, you should look to video games as ideal testbeds for the work you do. If you are a video game developer, you should look to AI for the technology that makes completely new types of games possible. This chapter lays out the case for both of these propositions. It asks the question "what can video games do for AI", and discusses how in particular general video game playing is the ideal testbed for artificial general intelligence research. It then asks the question "what can AI do for video games", and lays out a vision for what video games might look like if we had significantly more advanced AI at our disposal. The chapter is based on my keynote at IJCCI 2015, and is written in an attempt to be accessible to a broad audience.

Application projects, may it be in healthcare and the public sector or elsewhere, have the potential to advance foundational (“genuine”) artificial intelligence (AI) research. Unfortunately, insights from specific application projects are rarely propagated back to AI research. This article argues for ways to facilitate such backpropagation and how the contributions in this special issue enable exactly this backpropagation. It also addresses the challenges that come along with high-risk application project, which frequently occur in the area of healthcare and the public sector due to the sensitivity of the subjects.

There is increasingly much agreement in the cognitive sciences that human cognition is embodied &amp;ndash; to some significant extent. However, there is much less agreement regarding in what sense(s) cognition is embodied. In particular, there is much agreement that sensorimotor interaction with the environment is fundamental to cognition. From a historical perspective, this emphasis on the sensorimotor body is at least partly due to the crucial role that the conceptual shift in artificial intelligence (AI) research &amp;ndash; from computational to robotic models &amp;ndash; has played in the overall development of embodied cognitive science. Most embodied AI research, however, in particular work on symbol grounding and related approaches, reduces the body to a mere sensorimotor interface for internal processes that are still just as computational as they were 30&amp;ndash;40 years ago. In Harnad's terms, this type of AI has only gone from a computational to a robotic functionalism. In theory, this could be limited to AI research as such, but in practice the view of the physical body as the computational mind's sensorimotor interface to the world still pervades much of cognitive science and philosophy of mind. The argument presented here is that there are good reasons to say that at least today's robots are in fact not embodied &amp;ndash; in any sense that would allow for anything even close to human embodied cognition and intentionality &amp;ndash; and that this has implications for social interactions between humans and robots.

StarCraft II (SC2) is a real-time strategy science-fiction video game developed by Blizzard Entertainment. Known for its complex state space and open-source environment [8], SC2 has become a popular domain for Artificial Intelligence (AI) research. This paper leverages the advances in AI research from SC2 to build human-autonomy teaming (HAT) aids, AI-driven software tools for human interactivity, for players to improve their skills. The human-machine interface (HMI) that houses these tools breaks the game into different components and visually represents each HAT aid to increase situational awareness and decrease response time.