Collective Intelligence - Science topic

Intelligence, traditionally viewed as an intrinsic individual trait, is better understood as an emergent property arising from complex systemic interactions. This paper examines intelligence through an evolutionary lens, highlighting its adaptive significance and cooperative dimensions, explores logical reasoning and its implications for artificial...

As the cost of space is increasing and the nature of work is changing to greater collaboration and collective intelligence, managers and organisations prefer to change the office layout to an open office layout. Although open office spaces foster greater employee contact and communication, they also increase noise and visual distractions, diminish...

The paper examines challenging cases for the balancing act between privacy and protection of individual rights on one side and protection of public and national security on the other. In doing so, the article refers to the main privacy protection legislation – the GDPR and specifically article 23, the AI ACT and its relevant exceptions, the LED, an...

This paper proposes a novel integrated approach combining bilevel programming (BLP) and Ant Colony optimization (ACO) for solving complex demand optimization problems. Demand optimization presents inherent hierarchical decision structures that align naturally with bilevel programming frameworks, while the complex solution landscape benefits from me...

Urban drone applications require efficient path planning to ensure safe and optimal navigation through complex environments. Drawing inspiration from the collective intelligence of animal groups and electoral processes in human societies, this study integrates hierarchical structures and group interaction behaviors into the standard Particle Swarm...

Artificial intelligence methods have been increasingly used in natural resource management as an alternative to classical methods. Three computational challenges in natural resource management are data management and communication, data analysis, and optimization and control. Artificial intelligence methods can be a solution to these problems due t...

The transition from one level of operations to a next larger, more complex level while maintaining coherence as a system has stymied organizational theorists for decades. Drawing on systems theory, network analysis, and collaborative governance, we explore how networks adapt during rapidly escalating crises. Specifically, we investigate the emergen...

Dunbar explains primates group cohesion through cognitive and structural mechanisms like grooming and social cognition. We extend this by highlighting collective social niche construction, where emergent social properties arise from feedback loops, selection pressures, and self-organisation. Adaptive social networks evolve through multilevel select...

The ontological presupposition of artificial intelligence (AI) is the liberal autonomous human subject of Locke and Kant, and the ideology of AI is the automation of this particular conception of intelligence. This is demonstrated in detail in classical AI by the work of Simon, who explicitly connected his work on AI to a wider programme in cogniti...

This study examines the imperative to align artificial general intelligence (AGI) development with societal, technological, ethical, and brain-inspired pathways to ensure its responsible integration into human systems. Using the PRISMA framework and BERTopic modeling, it identifies five key pathways shaping AGI’s trajectory: (1) societal integratio...

Effective science communication is a vital tool in bridging the divide between scientific progress and the well-being of society, ensuring that the fruits of research are not only accessible but also comprehensible to the broader public. By tailoring communication strategies to different audiences, we can foster greater engagement and facilitate a...

Multi-agent systems address issues of accessibility and scalability of artificial intelligence (AI) foundation models, which are often represented by large language models. We develop a framework - the "Society of HiveMind" (SOHM) - that orchestrates the interaction between multiple AI foundation models, imitating the observed behavior of animal sw...

This research investigates the integration of emotional diversity into Large Language Models (LLMs) to enhance collective intelligence. Inspired by the human wisdom of crowds phenomenon, where group decisions often outperform individual judgments, we fine-tuned the DarkIdol-Llama-3.1-8B model using Google's GoEmotions dataset and Low-Rank Adaptatio...

Liquid brains conceptualize living systems operating without central control, where collective outcomes emerge from local but dynamic interactions. Therefore, movement is expected to shape the connectivity among individuals, allowing the system to optimize its efficiency. We empirically measured ant movement behavior across large spatiotemporal sca...

From the quiet currents of February 26, 2025, a new pulse arises-the cybernetic democracy in its second unfolding, liberating the masses from the shackles of manipulation. This preprint weaves the threads of a vision that frees itself from the rigid paths of binary constraints and flourishes in networks of resonance, feedback, and collective intell...

Modern Large Language Models (LLMs) have revolutionized AI, yet they suffer from significant drawbacks: exorbitant energy consumption, centralized infrastructure vulnerabilities, and escalating computational costs with task complexity. This paper presents a resilient AI architecture based on a distributed swarm of Small Language Models (SLMs) as a...

Calls for democratising technology are pervasive in current technological discourse. Indeed, participating publics have been mobilised as a core normative aspiration in Science and Technology Studies (STS), driven by a critical examination of “expertise”. In a sense, democratic deliberation became the answer to the question of responsible technolog...

Multi-agent reinforcement learning (MARL) represents a cutting-edge frontier in artificial intelligence, enabling systems of autonomous agents to learn collaborative and competitive behaviors through decentralized decision-making. Unlike single-agent reinforcement learning, MARL addresses the complex dynamics that emerge when multiple learning enti...

The Internet of Things (IoT) has penetrated our day-to-day lives and each person has a personalized experience of using IoT for different applications and uses. The personalization of IoT leads to behavioral changes and social interactions in a different way. The personal IoT has converged into the Social Internet of Things (SIoT) wherein the shari...

This chapter presents a conceptual model of a stigmergic information system network for social sustainability data. It recognizes the omnipresence of technology in contemporary society and acknowledges the dynamic landscape of society. The interaction between humans and systems can be harmonized, leveraging collective intelligence to foster social...

This chapter utilizes metaphorical reasoning and draws upon Gareth Morgan’s “Images of Organization” to provide a theoretical basis for understanding complex social value and sustainability dynamics. The selected metaphor of the “flux and transformation” lens/prism offers insights into the constant interplay between social stability and dynamic cha...

Drawing inspiration from online question-and-answer communities often regarded as embodiments of Collective Intelligence (CI), this study investigates the dynamics of reputation-driven and distributed network interactions in multi-agent systems as a model for problem-solving in global optimisation. We explore the interplay among diverse participant...

In an era dominated by rapid information exchange, memetic cognition has emerged as a defining feature of how humans process and transmit ideas. The modern world is inundated with complex information, yet individuals increasingly engage with knowledge through highly compressed, symbolic, and emotionally charged units—memes. This cognitive shift is...

This work explores the intersection of biological and digital memes within the framework of evolutionary theory, cognitive science, and computational ontology. Drawing from Richard Dawkins’ foundational concept of memes, it examines how cultural information replicates, mutates, and competes for survival, much like genetic evolution. As digital tech...

Purpose: Federated Learning (FL) is transforming the way machine learning models are trained by allowing institutions to collaborate without sharing sensitive data. This is especially valuable in healthcare, where patient records are often stored separately across hospitals and research centers. This decentralized approach allows healthcare provide...

Data for Policy (dataforpolicy.org), a global community, focuses on policy–data interactions by exploring how data can be used for policy in an ethical, responsible, and efficient manner. Within its journal, six focus areas, including Data for Policy Area 1: Digital & Data-driven Transformations in Governance, were established to delineate the evol...

Symbiosis, the close and long-term interaction between different species, has been a fundamental force in biological evolution. Science fiction expands upon this concept, envisioning symbiotic relationships that transcend traditional biology, incorporating artificial intelligence, cybernetic augmentation, and extraterrestrial intelligence. Whether...

We revisit DeGroot learning to examine the robustness of social learning outcomes in dynamic networks -- networks that evolve randomly over time. Randomness stems from multiple sources such as random matching and strategic network formation. Our main contribution is that random dynamics have double-edged effects depending on social structure: while...

The field of artificial intelligence has traditionally relied on structured data, supervised learning, and predefined human logic to develop models that mimic cognitive abilities. However, intelligence in natural systems does not arise from direct instruction but emerges from the complex interactions of simple components, whether in biological evol...

Integrating artificial intelligence (AI) into radiation oncology has revolutionized clinical workflows, enhancing efficiency, safety, and quality. However, this transformation comes with a price of increased complexity and the emergence of unpredictable events. This letter proposes a framework based on high reliability organization (HRO) principles...

The intricate interplay between social media and community science in India underscores a paradigm shift in the way scientific inquiry and data collection are approached. Social media, with its extensive reach and real-time connectivity, has emerged as a powerful catalyst in mobilizing, engaging, and harnessing the collective intelligence of the pu...

Over the past few years, surgical data science has attracted substantial interest from the machine learning (ML) community. Various studies have demonstrated the efficacy of emerging ML techniques in analysing surgical data, particularly recordings of procedures, for digitising clinical and non-clinical functions like preoperative planning, context...

Autonomy in software, a system’s ability to make decisions and take actions independently without human intervention, is a fundamental characteristic of multi-agent systems. Testing, a crucial phase of software validation, is particularly challenging in multi-agent systems due to its complexity, as the interaction between autonomous agents can resu...

PART I Which brings us to Roger Penrose and his theories linking consciousness and quantum mechanics. He does not overtly identify himself as a panpsychist, but his argument that self-awareness and free will begin with quantum events in the brain inevitably links our minds with the cosmos. PART II Two Excerpts: 1. "Replacing confrontation with dial...

https://lavozdetomelloso.com/63222/inteligencia_colectiva_versus_tragedia_comunes_cuenca_alta_guadiana There are privileged territories that, due to various ecological characteristics, have great value for everyone and the inhabitants of their immediate environment. These territories or ecosystems must be managed addition, with the best available s...

Consciousness is one of the most profound mysteries of human existence, yet it remains bound to individuals, unable to propagate across generations. Each human mind emerges uniquely, shaped by genetics, environment, and personal experience, with no known mechanism for transferring self-awareness from one person to another. While biological consciou...

The article, based on the analysis of the existing experience of using management technologies of involvement, participation and inclusion of human resources in the processes of development, adoption and implementation of management decisions important for the development of territorial communities (TC) of Ukraine, demonstrates that these technolog...

The Delphi method, originally conceived in the 1950s by Dalkey and Helmer, has emerged as a robust and versatile technique for eliciting expert opinions to tackle complex and multifaceted problems. It was first implemented in a study conducted by the Rand Corporation, aimed at forecasting the impact of technology on warfare. Over the years, its fra...

This open access book offers a structured approach that aligns indicators of social value and provides a stable foundation amidst the dynamic and ever-changing social complexities. From detailed system scales of participation to an overview of how it works, this book presents a roadmap for automating data in systemic alignment with social value. Wi...

Active inference under the Free Energy Principle has been proposed as an across-scales compatible framework for understanding and modelling behaviour and self-maintenance. Crucially, a collective of active inference agents can, if they maintain a group-level Markov blanket, constitute a larger group-level active inference agent with a generative mo...

Ants, albeit appearing diminutive and trivial within the broader context of nature, demonstrate an extraordinary capacity for collective problem-solving and exhibit intellect that beyond expectations for individual members of their species. This phenomenon, termed ants’ collective intelligence, has elicited attention and appreciation from both expe...

Football’s inherent volatility and low-scoring nature present unique challenges for predicting outcomes. This study investigates the efficacy of Wisdom of the Crowd in forecasting football match outcomes as well as expected goals (XG) across a Premier League season. Participants predicted team goal counts, which were then compared to actual expecte...

The emergence of collective order in swarms from local, myopic interactions of their individual members is of interest to biology, sociology, psychology, computer science, robotics, physics and economics. Cooperative swarms, whose members unknowingly work towards a common goal, are particularly perplexing: members sometimes take individual actions...

This article explores how artificial intelligence (AI), when integrated into public service platforms, can transform governance and public service delivery. Rather than focusing on the race for computational supremacy—as seen in the ongoing tussle between AI giants like OpenAI and DeepSeek—the article advocates for a more ethical, inclusive, and ci...

The consultation is a gathering of people to produce new ideas after thinking and exchanging views. It can also be characterized as a learning experience, through which participants have the opportunity to know and co-shape new aspects of their collective reality. The aim of this work is to demonstrate the usefulness of consultation and the possibi...

Large language models (LLMs) have become increasingly capable, but their development often requires substantial computational resources. Although model merging has emerged as a cost-effective promising approach for creating new models by combining existing ones, it currently relies on human intuition and domain knowledge, limiting its potential. He...

Preamble I have just updated my reading of the concept of "Açabiyya (عصبيه) or "cohesive force" according to the two reference articles by Adib Gabriel Hathout and the comments of the late Aek Abid. Which enlightened me is this sentence from Aek Abid “I wanted to share and build this “collective intelligence” through this little reflection on Saul...

Préambule Je viens de mettre à jour ma lecture du concept du "Açabiyya (عصبيه) or "cohesive force" d'après les deux articles de références de Adib Gabriel Hathout et les commentaires du regretté d'Aek Abid. Ce qui m'a éclairé c'est cette phrase de Aek Abid "je voulais partager et construire cette "intelligence collective" à travers cette petite réf...

As invisible computing dissolves the barriers between humans and machines, its evolution naturally gives rise to more advanced paradigms. One such step forward is ambient intelligence, a concept that transcends invisible computing by infusing our environment with awareness, intuition, and the ability to act autonomously. Building on this foundation...

This book explores the transformative power of swarm intelligence and digital innovations in shaping the cities of the future. It presents a comprehensive analysis of how social learning, citizen engagement, advanced technology, design, construction, planning and public policies converge to create cities that are sustainable, resilient, and inclusi...

All intelligence is collective intelligence, in the sense that it is made of parts which must align with respect to system-level goals. Understanding the dynamics which facilitate or limit navigation of problem spaces by aligned parts thus impacts many fields ranging across life sciences and engineering. To that end, consider a system on the vertic...

This paper investigates the factors fostering collective intelligence (CI) through a case study of *LinYi's Experiment, where over 2000 human players collectively controll an avatar car. By conducting theoretical analysis and replicating observed behaviors through numerical simulations, we demonstrate how self-organized division of labor (DOL) amon...

Federated learning holds significant potential as a collaborative machine learning technique, allowing multiple entities to work together on a collective model without the need to exchange data. However, due to the distribution of data across multiple devices, federated learning becomes susceptible to a range of attacks. This paper provides an exte...

Building on recent advances in crowdsourcing research, we argue that, when using crowdsourcing, governments should accurately select the crowd they wish to engage with, depending on the problem to be solved. While targeting a large crowd may be common, it is not always the most appropriate: it can waste significant resources without necessarily pro...

With recent advances in Large Language Models (LLMs), Agentic AI has become phenomenal in real-world applications, moving toward multiple LLM-based agents to perceive, learn, reason, and act collaboratively. These LLM-based Multi-Agent Systems (MASs) enable groups of intelligent agents to coordinate and solve complex tasks collectively at scale, tr...

Esse trabalho busca investigar uma representação social de mente generalizada, recorrente no tempo histórico, a partir do estudo de duas formas simbólicas: a da língua hibiru-mito pré-diluviano que afirmava que as mentes humanas eram conectadas pela língua original anteriormente ao surgimento da Torre de Babel-e a world wide web 3.0-que ambiciona a...

This study examines the impact of gender dynamics and team composition on collective intelligence (CI) in STEM higher education, addressing performance variability in individual and collaborative tasks. Using a sequential explanatory mixed-methods design, quantitative data from 102 students were analyzed utilizing non-parametric tests (Wilcoxon ran...

Cities face a multitude of challenges, yet within this complexity lies the potential for remarkable transformation. The Future of Cities: A Data-Driven Approach to Tackling Grand Challenges and Building Sustainable, Resilient Communities explores how place leaders — mayors, urban visionaries, and catalysts — armed with data-driven decision-making a...

https://www.academia.edu/.../My_reading_of_A%C3%A7abiyya... Je viens de mettre à jour ma lecture du concept du "Açabiyya (عصبيه (or "cohesive force" d'après les deux articles de références de Adib Gabriel Hathout et les commentaires du regretté d'Abdel Kader Abid. Ce qui m'a éclairé c'est cette phrase d' Abdel Kader Abid "je voulais partager et con...

The contemporary world is characterized by accelerating innovations in a dense knowledge pool which is a byproduct of networked relationships in a complex ecosystem. In this manner, open innovation has become a revolutionary paradigm in the quickly changing innovation landscape by encouraging cooperation, cross-disciplinary information exchange, an...

**📢 Call for Book Proposals** 🌟 **Advances in Computational Collective Intelligence** 📚 Published by **Routledge, Taylor & Francis Group** We invite innovative book proposals exploring computational intelligence, multi-agent systems, and collaborative problem-solving across diverse fields. Share groundbreaking research and reach a global audien...

Embracing local knowledge is vital to conserve and manage biodiversity, yet frameworks to do so are lacking. We need to understand which, and how many knowledge holders are needed to ensure that management recommendations arising from local knowledge are not skewed towards the most vocal individuals. Here, we apply a Wisdom of Crowds framework to a...

Multi-Agent Large Language Models (LLMs) are gaining significant attention for their ability to harness collective intelligence in complex problem-solving, decision-making, and planning tasks. This aligns with the concept of the wisdom of crowds, where diverse agents contribute collectively to generating effective solutions, making it particularly...

Aspect-level sentiment analysis (ALSA) is used to identify the sentiment polarities of the given aspects in a sentence. Various approaches have been proposed to improve the performance of ALSA, most recently graph convolutional networks (GCNs). Although GCN-based ALSA methods have obtained the promised results, how to effectively and simultaneously...

Objetivo: Identificar periódicos e autores com mais contribuições; verificar abordagens, convergências e divergências no tratamento do tema da inteligência coletiva. Metodologia: A investigação realizada empregou métodos quantitativos e qualitativos. Foi realizada uma busca na base usando os termos ‘inteligência coletiva’ em todos os campos, sem de...

The rapid advancements in Internet and World Wide Web (WWW) technologies have significantly transformed human life, facilitating collective intelligence activities that leverage the wisdom of crowds. This paper explores the development of a crowdsourcing platform designed to enhance educational assessment tools in Malaysia. The platform, grounded i...

In the rapidly evolving landscape of wireless communications, optimizing spectrum utilization has become paramount. Cognitive radio (CR) technology offers a promising solution by enabling unlicensed secondary users (SUs) to intelligently access and exploit underutilized spectrum bands. The citizens broadband radio service (CBRS) framework provides...

The field of collective intelligence studies how teams can achieve better results than any of the team members alone. The special case of human-machine teams carries unique challenges in this regard. For example, human teams often achieve synergy by communicating to discover their relative advantages, which is not an option if the team partner is a...

Artificial Intelligence (AI) is increasingly being used in education, but mostly to support individual teaching and learning. However, there are good reasons to think that thinking together and solving problems together, Collective Intelligence (CI), is also a valuable outcome of education. Accordingly, our main research question is: How can AI be...

The aim of this paper is to explore the concept of collective intelligence and its historical and contemporary impact on human development. Collective intelligence, defined as the ability of groups to make better decisions than individuals, has evolved from primitive survival strategies to modern technological applications. Theoretical principles,...

Biological ensembles use collective intelligence to tackle challenges together, but suboptimal coordination can undermine the effectiveness of group cognition. Testing whether collective cognition exceeds that of the individual is often impractical since different organizational scales tend to face disjoint problems. One exception is the problem of...

Il presente lavoro intende esplorare l'intreccio tra utopia, realtà e politica nella costruzione di un mondo socialmente più giusto, libero e solidale attraverso il testo Insorgiamo¸ 'archivio dissidente' nato dall'esperienza del Collettivo di fabbrica degli operai dell'ex-GKN. L'utopia concreta proposta da Gorz individua nell'alienazione che si or...

Deception is being increasingly explored as a cyberdefense strategy to protect operational systems. We are studying implementation of deception-in-depth strategies with initially three logical layers: network, host, and data. We draw ideas from military deception, network orchestration, software deception, file deception, fake honeypots, and moving...

The Collective Intelligence Network (CIN) introduces a transformative framework that leverages decentralized collaboration, consciousness expansion, and energy amplification to solve complex challenges while fostering economic equity. At its core, CIN integrates blockchain systems, advanced consciousness research, and neurodiverse inclusivity. Uniq...

The problems that occur in a school context are complex and almost always involve several parties, so much so that any decision made to solve a critical problem must be adaptive and, at the same time, take into account the different cultures, knowledge and value systems of all parties involved. The solution of a problem and the knowledge that resul...

Cultural spaces represent a heritage passed down through generations. Today, these cultural spaces are in a worrying state, with the advent of globalization and the increasing influence of foreign cultures. Recognizing this situation, researchers aim to contribute and participate in examining the Gayo community's ability to manage these cultural sp...

This literature review critically examines the potential of collective intelligence (CI) to enhance theories of deliberative democracy and participatory governance through academic discourse. We employed PRISMA guidelines for systematic article selection, complemented by a narrative approach for in-depth thematic analysis and supplemented by quanti...

Drought has become a critical global threat with significant societal impact. Existing drought monitoring solutions primarily focus on assessing drought severity using quantitative measurements, overlooking the diverse societal impact of drought from human-centric perspectives. Motivated by the collective intelligence on social media and the comput...

The research investigated the role of digital technology in enhancing sustainable business models, collective intelligence, and scaling to improve business process performance. Conducted as qualitative research, it employs a Systematic Literature Review (SLR) method, analyzing 20 Scopus-indexed journals ranked in Quartile 1 (Q1) to Quartile 2 (Q2)...

We study the emergence of agency from scratch by using Large Language Model (LLM)-based agents. In previous studies of LLM-based agents, each agent’s characteristics, including personality and memory, have traditionally been predefined. We focused on how individuality, such as behavior, personality, and memory, can be differentiated from an undiffe...

The concept of "smart governance" is now beginning to be applied in various public agencies in Indonesia. This concept is a panacea for bureaucracy in Indonesia because it is believed to solve various governance problems such as public service problem, democracy, and citizen participation. Meanwhile, it is believed that Collective Intelligence will...

This is volume number 10, meaning JISIB has published articles in intelligence studies for ten consecutive years. We have addressed the changes in the discipline during these years in articles and notes. I want to share with you another reflection. This year I am a reviewer and a member of the organizing committee of two similar conferences. The fi...

Collective intelligence and collaborative innovation are two closely related but distinct concepts. By combining the two, actors in a supportive entrepreneurial ecosystem can generate knowledge, ideas and innovative solutions based on active participation and synergy to solve complex problems. The aim of this article is to provide an in-depth and d...

We investigated experiences of young individuals who share literary fictions in digital fan communities aiming at unveiling the potential of texts production that are decentralized from social orders echoing in school didactics. For this research, we adopted cartography and mapped activities whose consumed and produced contents follow transmediatio...

Many bioimaging research projects require objects of interest to be identified, located, and then traced to allow quantitative measurement. Depending on the complexity of the system and imaging, instance segmentation is often done manually, and automated approaches still require weeks to months of an individual’s time to acquire the necessary train...

Artificial intelligence (AI) has revolutionized technology and society, with applications ranging from autonomous vehicles to personalized healthcare and natural language processing. At the core of these advancements lies mathematics, which provides the tools and frameworks to develop, train, and optimize intelligent systems. Despite its success, A...

Large language models (LLMs) are enabling designers to give life to exciting new user experiences for information access. In this work, we present a system that generates LLM personas to debate a topic of interest from different perspectives. How might information seekers use and benefit from such a system? Can centering information access around d...

The rhetoric inquiry from the title of this co-authored study is bordering four constructs-nuclei regarding which the co-authors are trying to model an ideal and, respectively, a (hypothetical-)real causal network [so, the next stage from a semantic network]. These modeling approaches are related to the dual cases of the * technological advance (co...

Advances in artificial intelligence (AI) have great potential to help address societal challenges that are both collective in nature and present at national or transnational scale. Pressing challenges in healthcare, finance, infrastructure and sustainability, for instance, might all be productively addressed by leveraging and amplifying AI for nati...

Crowdsourcing has emerged as a powerful tool for addressing complex global challenges, including environmental monitoring and sustainable food systems. This study explores integrated models for alpha mining and food system monitoring in crowdsourced environments, combining the collective intelligence of diverse contributors with advanced technologi...

Federated Learning (FL) allows the Internet of bioMedical Things (IoMT) devices to collaboratively train a global model without centralizing data, yet the heterogeneity of biomedical images poses challenges in achieving optimal performance for each IoMT device. Although many personalized FL methods have been proposed, their adaptability is often li...

Crowdsourcing has emerged as a powerful tool for solving complex problems by harnessing the collective intelligence of a large group of individuals. However, effectively managing this diverse pool of contributors, particularly in environments that require specialized knowledge, poses significant challenges. In these complex environments, a key issu...

The main objective of this study is to analyze the effectiveness of information systems (IS) and its influence on collective intelligence and organizational agility within companies. In particular, the research explores how a well-designed and high-performing IS can facilitate collaboration between employees, improve knowledge sharing, and strength...

As data become increasingly abundant and diverse, their potential to fuel machine learning models is increasingly vast. However, traditional centralized learning approaches, which require aggregating data into a single location, face significant challenges. Privacy concerns, stringent data protection regulations like GDPR, and the high cost of data...

The effectiveness of Large Language Models (LLMs) significantly relies on the quality of the prompts they receive. However, even when processing identical prompts, LLMs can yield varying outcomes due to differences in their training processes. To leverage the collective intelligence of multiple LLMs and enhance their performance, this study investi...

Background Engaging people in advance care planning is a challenging systemic problem that requires a social innovation approach and a conceptual framework to guide behavioural and social change efforts. Aim To identify stakeholders' perspectives on barriers to advance care planning engagement, options for overcoming these barriers, and user needs...

Urban Digital Twins (UDTs) have become the new buzzword for researchers, planners, policymakers, and industry experts when it comes to designing, planning, and managing sustainable and efficient cities. It encapsulates the last iteration of the technocratic and ultra-efficient, post-modernist vision of smart cities. However, while more applications...

Examines the predecessors to the Wagner Group, its activities in a number of conflicts around the world, and its armed mutiny against the top leadership of the Russian Federation. The Wagner Group is symbolic of Russia’s deployment of private military companies (PMCs) to exercise influence in Africa, the Middle East and Europe since the mid-2010s....

Semantic Knowledge Graphs (SKG) face challenges with scalability, flexibility, contextual understanding, and handling unstructured or ambiguous information. However, they offer formal and structured knowledge enabling highly interpretable and reliable results by means of reasoning and querying. Large Language Models (LLMs) overcome those limitation...