Dois membros do DI/NOVA LINCS no top mundial
04-02-2021
Foi recentemente publicado um estudo, liderado por John Ioannidis, professor da Universidade de Stanford, com uma lista dos cientistas mais citados a nível mundial, no topo 2% das respetivas áreas, que inclui 384 investigadores portugueses, dos quais 30 são da Universidade NOVA de Lisboa.
Dessa lista fazem parte o Prof. Luís Moniz Pereira e o Prof. Luís Caires, ambos membros do Departamento de Informática e do NOVA LINCS.O trabalho, agora divulgado, baseia-se em métricas de citação padronizadas mais precisas, com o propósito de combater os abusos de autocitação. O número de citações permite avaliar o impacto e influência consolidada de um determinado cientista ou instituição no progresso do conhecimento científico.O trabalho pode ser consultado aqui.
Category: [rede.APPIA]
A [rede.APPIA] é a lista de distribuição de correio electrónico da APPIA, com o objectivo de divulgar notícias de interesse para a comunidade científica da Inteligência Artificial, disponível através do endereço rede [at] appia [ponto] pt.
[rede.APPIA] Who Is Winning the AI Race: China, the EU or the United States?
[rede.APPIA] Fwd: [Infos] [Iai-societies] IJCAI-21 Call for Demos
[rede.APPIA] Mediating artificial intelligence developments through negative and positive incentives
“Mediating artificial intelligence developments through negative and positive incentives”
[rede.APPIA] DaSSWeb – Data Science and Statistics Webinar – 26 Jan – Alípio Jorge
DaSSWeb – Data Science and Statistics Webinar
Tuesday, 26 January, 14:30
Speaker: Alípio M. Jorge Fac. Sciences, Univ. Porto & LIAAD INESC TEC
Title: Text2Story: Narrative Extraction from Texts
Zoom link: videoconf-colibri.zoom.us/j/85023733490
Abstract:
Nowadays journalistic content is distributed in multiple formats, mostly through the web and specific internet based applications running on smartphones and tablets. Text is a very important format, but readers (or more accurately users or information consumers) heavily rely on images, videos, slideshows, charts and infographics. Textual content is still the main representation for information. Any journalistic subject (e.g. Trump and Russia) is described in one or more texts produced by journalists and possibly commented by readers. Many of those subjects are followed during days, weeks or months. To grasp a possibly vast and somewhat complex set of interconnected news articles, readers would greatly benefit from tools that summarize those articles by showing main actors, their interplay and their trajectories in time and space, their motivations, main events, causal relations of events and outcomes. In other words, tools that extract narrative elements and re-represent them in formats that convey the essential story but that are more efficiently consumed by the users. In this talk I will talk about these research challenges and current state of the art.
[rede.APPIA] Entropy | Special Issue : Artificial Intelligence in Dynamics of Human Cooperation
Special Issue Editors
Dr. The Anh Han Website
Guest EditorSchool of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK
Interests: evolutionary game theory; dynamics of human cooperation; AI; cognitive modeling; agent-based simulationsDr. Simon Powers Website
Guest EditorSchool of Computing, Edinburgh Napier University, Edinburgh EH11 4DY, UK
Interests: institutions; social dilemmas; multi-agent systems; cultural evolution; game theory; evolutionary game theoryProf. Dr. Luís Moniz Pereira Website
Guest EditorDepartamento de Informática, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Campus de Caparica, 2829-516 Caparica, Portugal
Interests: knowledge representation and reasoning; logic programming; cognitive sciences; evolutionary game theory; machine ethics; computer science philosophyDepartment of Business Administration, Soka University, Tangi 1-236, Hachioji, Tokyo 192-8577, Japan
Interests: social dilemmas; evolution of cooperation; evolutionary game theory; indirect reciprocity; agent-based simulations; computational social science
Special Issues and Collections in MDPI journalsDear Colleagues,
The problem of the evolution of cooperation and the emergence of collective behavior, which cuts across diverse disciplines such as Economics, Physics, Biology, Psychology, Sociology, Political, plus Cognitive and Computer Sciences, remains one of the greatest integrative interdisciplinary challenges facing science today. Mathematical and simulation techniques including evolutionary game theory, statistical physics, and agent-based simulations have proven powerful to study this problem. To understand the evolutionary mechanisms that promote and more or less stably maintain collective behavior in various societies, it is important to take into account the intrinsic complexity of individuals partaking therein, namely their cognitive and complex decision-making processes. On the other hand, artificial intelligence (AI) and related technologies have become increasingly prevalent in human life, making decisions that might alter the dynamics of human interactions in many ways. Moreover, there exists a double-edged sword: what cognition affords collective advantageous communities and vice-versa, what cognitive abilities are advantageously selected or enhanced in a collective community of what structure.
This Special Issue aims to provide a forum for the exploration of the potential interplay between AI and the dynamics of human collective behavior such as cooperation, coordination, trust and fairness; in particular, the different ways that the advancement of AI might alter the dynamics of human collective behavior, and vice-versa. Both theoretical modeling and behavioral experiment studies are welcome.
Some potential topics include (but are not limited to):
- Cooperation in hybrid societies;
- Cooperation with autonomous agents;
- AI-based cooperation engineering;
- Trust and cooperation in human–machine interactions;
- Cognitive mechanisms and cooperation;
- Emergence of the cognitive mechanisms for cooperation;
- Reputation and information processing;
- Cooperation and competition in AI development;
- Incentives design for pro-sociality in human-agent societies;
- AI and social cohesion.
Dr. The Anh Han
Dr. Simon Powers
Prof. Dr. Luís Moniz Pereira
Prof. Dr. Isamu Okada
Guest EditorsManuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI’s English editing service prior to publication or during author revisions.
[rede.APPIA] Fwd: A New Journal from ACM Co-published with Sage: Collective Intelligence
Begin forwarded message:
From: “Collective Intelligence Co-Editors-in-Chief (do not reply)” <call-for-papers@hq.acm.org>Subject: A New Journal from ACM Co-published with Sage: Collective IntelligenceDate: 11 January 2021 at 15:30:00 WETTo: lmp@FCT.UNL.PT
ACM Digital Library
A New Journal from ACM – Collective Intelligence
Collective Intelligence, co-published by ACM and SAGE, with the collaboration of Nesta, is a global, peer-reviewed, open-access journal devoted to advancing the theoretical and empirical understanding of collective performance in diverse systems. These systems can include human organizations, hybrid AI-human teams, computer networks, adaptive matter, cellular systems, neural circuits, animal societies, nanobot swarms, and others. The journal embraces a policy of creative rigor in the study of collective intelligence to facilitate the discovery of principles that apply across scales and new ways of harnessing the collective to improve social, ecological, and economic outcomes. In that spirit, the journal encourages a broad-minded approach to collective performance. It welcomes perspectives that emphasize traditional views of intelligence as well as optimality, satisficing, robustness, adaptability, and wisdom.
In more technical terms, this includes issues related to collective output quality and assessment, aggregation of information and related topics (e.g., network structure and dynamics, higher-order vs. pairwise interactions, spatial and temporal synchronization, diversity, etc.), accumulation of information by individuals/components, environmental complexity, evolutionary considerations, and design of systems and platforms fostering collective intelligence.
Each article accepted after peer review is made freely available online immediately upon publication, is published under a Creative Commons license, and will be hosted online in perpetuity. Nesta is sponsoring the Article Processing Charges (APCs) for the Journal in its launch year. As a result, the APCs for this Journal are currently waived for the first year of publication.
For more information and to submit your work, please visit dl.acm.org/journal/colint.
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