[rede.APPIA] – Page 43

[rede.APPIA] Entropy | Special Issue : Artificial Intelligence in Dynamics of Human Cooperation

2021-01-192021-03-01 Luís Moniz Pereira

Please divulge.

Entropy | Special Issue : Artificial Intelligence in Dynamics of Human Cooperation

https://www.mdpi.com/journal/entropy/special_issues/Dyn_Hum_Coop

Special Issue Editors

Dr. The Anh Han Website
Guest Editor

School 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 simulations

Dr. Simon Powers Website
Guest Editor

School of Computing, Edinburgh Napier University, Edinburgh EH11 4DY, UK
Interests: institutions; social dilemmas; multi-agent systems; cultural evolution; game theory; evolutionary game theory

Prof. Dr. Luís Moniz Pereira Website
Guest Editor

Departamento 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 philosophy

Prof. Dr. Isamu Okada Website
Guest Editor

Department 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 journals

Dear 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 Editors

Manuscript 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

2021-01-122021-03-01 Luís Moniz Pereira

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 Intelligence

Date: 11 January 2021 at 15:30:00 WET

To: 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

2021-01-052021-03-01 Fernando Santos

** 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.

*******************************************************

Adaptive and Learning Agents Workshop at AAMAS (London, UK – Virtual)

https://ala2021.vub.ac.be

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).

*******************************************************

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

*******************************************************

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

*******************************************************

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.

*******************************************************

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

2021-01-052021-03-01 Maria Paula Brito Silva

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.
***********************************************************************
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>

DaSSWeb_Elisabeth_Fernandes.pdf

[rede.APPIA] IEEE/ACM/ASA DSAA’2021: CALL FOR SPECIAL SESSION PROPOSALS

2020-12-152021-03-01 Carlos Manuel Abreu Gomes Ferreira

======================================================================
IEEE/ACM/ASA DSAA’2021
CALL FOR SPECIAL SESSION PROPOSALS

dsaa2021.dcc.fc.up.pt/calls/special-sessions
======================================================================

Important Dates
——————————————————————————
* Special Session Proposal Due: 21 February 2021
* Special Session Proposal Notification: 28 February 2021
* Paper Submission Deadline: as for the main conference 23 May 2021
* Special Session Paper Notification: as for the main conference 25 July 2021

About DSAA Special Sessions ——————————————————————————
DSAA Special Sessions are an important part of the main conference program. They bring together researchers, industry experts, practitioners, and potential users who are interested in cultivating specialized and important aspects of data science and analytics.

DSAA Special Sessions are intended to promote EMERGING data science research areas that are not well established and covered in the main conference tracks, while featuring much higher quality, integrity and impact of presentations than classic workshops typically hosted in all major conferences. The same evaluation criteria and quality level apply as for the main conference, but the papers must adhere to the area of the special session they are submitted to, and the reviewers are experts in that area.

Many real-world challenges call for interdisciplinary solutions and a dialog of cultures. In DSAA 2021, we particularly encourage proposals for special sessions that promote such a dialog, e.g. on statistics and data mining, pattern recognition and statistics, data mining and simulation.

We welcome proposals that promote a more intensive interaction between different communities and proposals that promote cooperation to solve interdisciplinary problems. Proposals on special sessions on how interdisciplinary data science can make the world stronger against disease, outbreaks are strongly encouraged.

Thus, special sessions might focus on:

a) topics on the border of data science research area,
b) advanced topics within the data science research area, or
c) specific application areas for data science.

Special Session Proposal Submission and Review
——————————————————————————
Proposals for hosting special sessions at DSAA 2021 are welcome. The proposals must address:

(1) Title
(2) Aims and scope
(3) Topics of interest
(4) Relevance to the DSAA main conference tracks and topics
(5) Organizers
(6) Past special sessions or relevant experiences or track records
(7) Potential committee members
(8) Potential invited speakers

For each organizer in (5), provide name, affiliation, country, email and a short biographical sketch, describing relevant qualifications and experience; identify at least one organizer as the contact person.

For (6), list any special session or relevant events (e.g., workshops) the organizers have organized in recent years in DSAA or other major conferences; for each, list the year, the conference, number of submissions, number of papers accepted, number of participants, etc.

For (7), give a list of qualified committee members who would be invited.

For (8), please provide the names of one or two authoritative speakers that could open the special session, and that can deliver a comprehensive overview of the topic of interest.

Special session proposals will be reviewed based on the above criteria and quality of the proposals as well as their relationship to the main conference topics. Preference may be given to timely topics that are critical for data science and analytics, inspire highly interactive discussions, and showcase the impact of data science and analytics.

Proposers are encouraged to give an estimation of the number of submissions they expect.

Submission of a special session:
——————————————
cmt3.research.microsoft.com/DSAA2021
Carlos Ferreira
ISEP | Instituto Superior de Engenharia do Porto Rua Dr. António Bernardino de Almeida, 431 4249-015 Porto – PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail@isep.ipp.pt | www.isep.ipp.pt

[rede.APPIA] DaSSWeb – Data Science and Statistics Webinar – 15Dez – Soraia Pereira

2020-12-102021-03-01 Maria Paula Brito Silva

DaSSWeb – Data Science and Statistics Webinar
Tuesday, 15 December, 14:30
Speaker: Soraia Pereira CEAUL
Title: Statistical Learning for drivers of moderate and extreme rainfall
Zoom Link : videoconf-colibri.zoom.us/j/82950361641
Abstract:
Madeira has suffered a variety of extreme rainfall events over the last two centuries, including the flash floods of October 1803 (800–1000 casualties) and those of February 2010—the latter with a death toll of 45 people and with an estimated damage of 1.4 billion Euro. But what are the drivers of moderate and extreme rainfall in Madeira? In this talk I will devise a methodology for assessing this question, by resorting to tools, methods, and concepts at the interface between Statistical Learning and Statistics of Extremes. Our proposed model allows to identify which drivers are significant to explain the moderate rainfall but not to explain the extreme rainfall and viceversa.

***********************************************************************

DaSSWeb_Soraia_Pereira.pdf

[rede.APPIA] CFP: Special Issue on Foundations of Data Science – Machine Learning Journal

2020-12-092021-03-01 Carlos Manuel Abreu Gomes Ferreira

Special Issue on Foundations of Data Science – Machine Learning Journal

Data science is currently a very active topic with an extensive scope, both in terms of theory and
applications. Machine Learning is one of its core foundational pillars. Simultaneously, Data Science
applications provide important challenges that can often be addressed only with innovative Machine
Learning algorithms and methodologies. This special issue focuses on the latest developments in
Machine Learning foundations of data science, as well as on the synergy between data science and
machine learning. We welcome new developments in statistics, mathematics and computing that
are relevant for data science from a machine learning perspective, including foundations, systems,
innovative applications and other research contributions related to the overall design of machine
learning and models and algorithms that are relevant for data science. Theoretically well-founded
contributions and their real-world applications in laying new foundations for machine learning and
data science are welcome.

This special issue solicits the attention of a broad research audience. Since it brings together a variety
of foundational issues and real-world best practices, it is also relevant to practitioners and engineers
interested in machine learning and data science.

Accepted papers will be presented at the IEEE DSAA conference in Porto, October 2021.