Our most recent publication, in PLoS ONE open access:
“Mediating artificial intelligence developments through negative and positive incentives”
“Mediating artificial intelligence developments through negative and positive incentives”
Luis
Month: January 2021
[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.
DaSSWeb_Alipio_Jorge.pdf[rede.APPIA] Entropy | Special Issue : Artificial Intelligence in Dynamics of Human Cooperation
Please divulge.
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
FYI
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.
Association for Computing Machinery
1601 Broadway, 10th Floor, New York, NY 10019
Copyright © 2021, ACM, Inc. All rights reserved
[rede.APPIA] Adaptive and Learning Agents Workshop (AAMAS 2021) – Call for Papers
** Apologies if you receive more than one copy. Please share with students and colleagues. **
Dear all,
We are organizing the next iteration of the Adaptive and Learning Agents (ALA) workshop at the International Conference on Autonomous Agents and Multiagent Systems (AAMAS) in London (Virtual). Please find the CfP below.
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Adaptive and Learning Agents Workshop at AAMAS (London, UK – Virtual)
Submission deadline: February 10, 2021
Extended versions of all original contributions at ALA 2021 will be eligible for inclusion in a special issue of the Springer journal Neural Computing and Applications (Impact Factor 4.774).
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TL;DR:
* Workshop with a long and successful history, now in its thirteenth edition.
* Covering all aspects of adaptive and learning agents and multi-agent systems research.
* Open to original research papers, work-in-progress, and visionary outlook papers, as well as presentations on recently published journal papers.
* ACM proceedings (AAMAS) format up to 8 pages (excluding references) for original research, up to 6 pages for work-in-progress and outlook papers (shorter papers are also welcome and will not be judged differently) and 2 pages for recently published journal papers.
* Accepted papers are eligible for inclusion in a post-proceedings journal special issue.
* Submissions through easychair: https://easychair.org/conferences/?conf=ala2021
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IMPORTANT DATES:
* Submission Deadline: February 10, 2021
* Notification of acceptance: March 10, 2021
* Camera-ready copies: March 24, 2021
* Workshop: May 3 & 4, 2021
* Extended submission deadline: September 15, 2021
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OVERVIEW
Adaptive and learning agents, particularly those interacting with each other in a multi-agent setting, are becoming increasingly prominent as the size and complexity of real-world systems grows. How to adaptively control, coordinate and optimize such systems is an emerging multi-disciplinary research area at the intersection of Computer Science, Control Theory, Economics, and Biology. The ALA workshop will focus on agents and multi-agent systems which employ learning or adaptation.
The goal of this workshop is to increase awareness of and interest in adaptive agent research, encourage collaboration and give a representative overview of current research in the area of adaptive and learning agents and multi-agent systems. It aims at bringing together not only scientists from different areas of computer science but also from different fields studying similar concepts (e.g., game theory, bio-inspired control, mechanism design).
This workshop will focus on all aspects of adaptive and learning agents and multi-agent systems with a particular emphasis on how to modify established learning techniques and/or create new learning paradigms to address the many challenges presented by complex real-world problems.
The topics of interest include but are not limited to:
* Novel combinations of reinforcement and supervised learning approaches
* Integrated learning approaches using reasoning modules like negotiation, trust, coordination, etc.
* Supervised and semi-supervised multi-agent learning
* Reinforcement learning in multi-agent systems
* Novel deep learning approaches for adaptive single and multi-agents systems
* Human-in-the-loop learning systems
* Planning and Reasoning (single and multi-agent)
* Distributed learning
* Adaptation and learning in dynamic environments
* Evolution and Co-evolution of agents in complex multi-agent environments
* Cooperative exploration
* Learning to cooperate and collaborate
* Learning trust and reputation
* Communication restrictions and their impact on multi-agent coordination
* Design of reward structure and fitness measures for coordination
* Scaling learning techniques to large systems of agents
* Emergent behavior in adaptive multi-agent systems
* Game theoretical analysis of adaptive multi-agent systems
* Neuro-control for adaptation in multi-agent systems
* Bio-inspired multi-agent systems
* Adaptive and learning agents for multi-objective decision making
* Multiple objectives in (multi-)agent systems
* Applications of adaptive agents, learning agents, and multi-agent systems to real world complex systems
In addition to these topics, this year we are particularly interested in exploring negative results that can serve as guidelines for early-stage researchers in the field of adaptive and learning single/multi-agent systems.
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SUBMISSION DETAILS
Papers can be submitted through EasyChair: https://easychair.org/conferences/?conf=ala2021
We invite submission of original work, up to 8 pages in length (excluding references) in the ACM proceedings format (i.e. following the AAMAS formatting instructions). This includes work that has been accepted as a poster/extended abstract at the AAMAS 2021 conference. Additionally, we welcome submission of preliminary results, i.e. work-in-progress, as well as visionary outlook papers that lay out directions for future research in a specific area, both up to 6 pages in length, although shorter papers are very much welcome, and will not be judged differently. Finally, we also accept recently published journal papers in the form of a 2 page abstract.
All submissions will be peer-reviewed (single-blind). Accepted work will be allocated time for poster and possibly oral presentation during the workshop. Extended versions of all original contributions at ALA 2021 will be eligible for inclusion in a special issue of the Springer journal Neural Computing and Applications (Impact Factor 4.774). Deadline for submitting extended papers: September 15, 2021.
We look forward to receiving your submissions,
– The Organizers
Conor F. Hayes (NUI Galway, IE)
Roxana Rădulescu (Vrije Universiteit Brussel, BE)
Diederik M. Roijers (Vrije Universiteit Brussel, BE & HU University of Applied Sciences Utrecht, NL)
Fernando P. Santos (Princeton University, USA)
Felipe Leno da Silva (University of São Paulo, BR)
[rede.APPIA] DaSSWeb – Data Science and Statistics Webinar – 12 Jan – Elisabeth Fernandes
DaSSWeb – Data Science and Statistics Webinar
Tuesday, 12 January, 14:30
Speaker: Elisabeth Fernandes (Público Comunicação Social S.A. & Instituto Universitário de Lisboa (ISCTE-UIL), ISTAR)
Title: Data Analysis at Público
Zoom Link : videoconf-colibri.zoom.us/j/89142347854
Abstract:
The digital era brought new challenges and opportunities to newspapers. The transition from a single medium to a multimedia approach is a path that requires the perfect combination between quality journalism, technology and data.
The traditional publication frequency has been surpassed by a new digital dynamic minute by minute. The reader has access the information, in more channels, in different formats. The narrative control passed from the narrator to the reader. Media companies have large amounts of data with high investments in technology. Data Analysis gained a new protagonism inside the newsrooms, particularly at Público. New daily words like recirculation, engagement and dashboards become part of daily life. In this presentation, we aim to share the recent history of Público’s digital transformation and how data analysis helped to achieve company goals.
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Paula Brito Tel. (direct): (+351) 220426473 Faculdade de Economia Tel. (central FEP): (+351) 2205571100 Universidade do Porto Tel. (internal line): 4573 Rua Dr. Roberto Frias Fax: (+351) 225505050 4200-464 Porto e-mail: mpbrito@fep.up.pt<mailto:mpbrito@fep.up.pt> PORTUGAL www.fep.up.pt/docentes/mpbrito<www.fep.up.pt/docentes/mpbrito>