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.
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Deadline for full paper submission: 6th August, 2021
Notification of acceptance: 17th September, 2021
Camera-Ready papers: 15th October, 2021
Conference: 4-7 December 2021
Submissions:
SSCI welcomes full length papers of 6 to 8 pages, in IEEE two-column conference style. Please refer to https://attend.ieee.org/ssci-2021/submission/ for submission and paper preparation details.
Scope:
The energy sector is undergoing major changes, namely regarding new concepts and principles for economic and environmentally friendly operations and planning, technological upgrades, and new forms for end-users’ behaviour. Electricity is a key driver of modern societies, and consumers expect it to be available at every moment of the day. This expectation is kept even considering increasing demand, environmental restrictions, increasing use of non-dispatchable energy sources, technical issues and many other factors that may negatively impact the sector’s efficiency. This energy transition is requiring the entire sector to adapt itself. New operation and business models are required, as well as new infrastructure and new technological means.
Computational intelligence based approaches are of crucial to address major challenges for highly automated and robust operations in a very dynamic, complex, and competitive environment such as the power and energy sectors, especially in a time of accelerated energy transition.
This special session aims at bringing together different experiences in the application of computational intelligence based approaches to power and energy problems, targeting the contribution of the main international experts in the field, both from academia and industry. Although focused on the application domain of power and energy systems, this special session envisages a broad spectrum of computational intelligence based approaches that address some of the most prominent problems in the field.
Submission Topics:
·Agent-based Smart Grid Simulation
·Big Data Applications for Energy Systems
·Coalitions and Aggregations of Smart Grid and Market Players
·Consumer Profiling
·Context Aware Systems
·Data-Mining Approaches in Smart Grids
·Decision Support Approaches for Smart Grids
·Demand Response Aggregation
·Demand Response Integration in the Market
·Demand Response Remuneration Methods
·Electric vehicles
·Electricity Market Modelling and Simulation
·Electricity Market Negotiation Strategies
·Energy Resource Management and Optimization in Buildings
·Information technology applications
·Innovative Demand Response Models and Programs
·Innovative Energy Tariffs
·Integration of Electric Vehicles in the Power System
·Intelligent Approaches for Microgrid Management
·Intelligent Home Management Systems
·Intelligent methods for Demand Management
·Intelligent Resources Scheduling
·Intelligent Supervisory Control Systems
·Knowledge-based approaches for Power and Energy Systems
·Load Forecast
·Multi-Agent Applications for Smart Grids
·Multi-Agent Systems in Power and Energy Systems
·Other Computational Intelligence-based Methods for Power and Energy Systems
·Phasor Measurement Units Applications
·Real-time simulation
·Reliability, Protection and Network Security Methods
·Renewable Energy Forecast using Computational Intelligence
·Semantic communication and data
·Smart Sensors and Advanced Metering Infrastructure
Special Session Organizers:
·José Rueda, Technische Universiteit Delft, The Netherlands
We would like to draw your attention to a special issue that we are organizing on Trustworthy Adaptive and Learning Agents in the Springer AI and Ethics (AI&E) journal.
Below (and here) you can find the call for papers with extra information.
[apologies for cross-posting]
Kind regards,
Patrick Mannion
Fernando P. Santos
Diederik M. Roijers
—
Topical Collection on Trustworthy Adaptive and Learning Agents
As autonomous agent-based systems become ever more prevalent in everyday life, it is imperative that society can trust that such systems will act for the benefit of humanity. Ensuring trustworthiness for autonomous systems is one of the key global challenges facing society at present, as evidenced by recently published guidelines on the topic by organisations such as the European Commission, the IEEE, and the OECD. Trustworthiness has a number of different dimensions, including explainability, safety, fairness, accountability and compliance with legislative and ethical standards.
Autonomous agents operating in the real world should therefore make decisions in a fair and transparent manner that respects ethical principles, should be aware of their social environment and should comply with applicable regulations. This can prove challenging given the complexity of agent architectures and the long-term dynamics — often hard to anticipate and control — resulting from multiple agents learning and adapting to each other and to constantly changing environments. Furthermore, the majority of published research on autonomous agents does not explicitly consider the level of trustworthiness of the proposed approaches, leaving a vast gap in the literature between the theory and practical application of agent-based systems.
Learning and adaptation are key capabilities for autonomous systems. This topical collection (TC) in the AI and Ethics (AI&E) journal focuses on the topic of Trustworthy Adaptive and Learning Agents (TALA). AI&E is a new journal recently launched by Springer, and seeks to promote informed debate and discussion of the ethical, regulatory, and policy implications that arise from the development of AI. The TALA TC targets high-quality original papers covering all aspects of trustworthiness in agent-based systems, including, but not limited to, the list of topics below. Manuscripts that extend a previous conference or workshop publication are welcome, provided that there is a significant amount of new material in the submission (i.e., the manuscript should contain at least 30% new material).
This topical collection is associated with the long-running and successful series of workshops on Adaptive and Learning Agents (ALA), that have been held each year since 2009 in conjunction with the AAMAS conference. Therefore, manuscripts reporting extended versions of work presented at a prior edition of the ALA workshop are very much welcome. The TALA TC has an open call for papers; it is not necessary to submit preliminary work to the ALA workshop in order to have your manuscript considered for publication in this TC.
Topics
The following is a non-exhaustive list of topics that we would like to cover in the special issue:
Trustworthy algorithms for ALA, including those based on reinforcement learning and planning
Principled approaches to reward design for trustworthy ALA
Trustworthy multi-agent decision making
Requirements and design principles for trustworthy ALA
Benchmark problems for verifying trustworthiness of ALA
Multi-objective decision making approaches to TALA
Analyses of TALA from different ethical paradigms (such as utilitarianism, deontology, particularism, etc.).
Handling (environmental epistemic and aleatoric) uncertainty in TALA
Safe reinforcement learning
Explainable (learning) agents
Avoidance of bias in ALA
Emergence of coordination among adaptive and learning agents towards societal and environmental well-being
Long-term trustworthiness in dynamic environments composed of learning agents
Game theoretic approaches to frame ethical dilemmas in multiagent systems
Agent-based approaches to model the societal impacts of AI
Compliance of ALA with regulations, ethics and/or social norms
Methods to counter malicious effects of autonomous agents (e.g., preventing misinformation through bots on social media)
Perspectives on cultural differences in accepting and trusting autonomous learning agents
Approaches to audit the behavior and impact of ALA, including agent failures
Guest Editors
Patrick Mannion (Lead Guest Editor), School of Computer Science, National University of Ireland Galway, webpage, email: patrick.mannion@nuigalway.ie
Diederik M. Roijers, Vrije Universiteit Brussel & HU University of Applied Sciences Utrecht, webpage, email: diederik.roijers@vub.be
Timeline
There is no specific submission deadline for this TC. Manuscript submissions will be considered for publication in the TALA TC on a continuous basis until a sufficient number of manuscripts have been accepted for publication. Manuscripts will be sent out for review as soon as they are received, and first decisions on manuscripts can be expected within 2 months approx. from the initial submission date. Submissions accepted for publication before the completion of the topical collection will be published online on the journal website shortly after acceptance. Authors considering submitting to the TALA TC should contact the Guest Editors in advance, to ensure that their proposed manuscript is in scope, and that there is space in the TC for the manuscript.
Article types
This TC solicits original research articles, reviews/surveys, and opinion pieces/commentaries relating to trustworthiness in agent-based systems, including those that employ learning and/or adaptation. Research articles should present original and high-quality theoretical and/or empirical results that advance the field of Trustworthy Adaptive and Learning Agents. It is expected that original research articles include (as appropriate) full Introduction, Background, Related Work, Methods, Results, and Discussion sections. Reviews/surveys should provide a comprehensive summary of a research topic of interest to TALA, and identify open challenges and new research directions for the field based on a thorough analysis of current literature. Opinion pieces/commentaries should offer new personal perspectives, visionary ideas, current challenges or summarize new research opportunities on a topic related to TALA, be circa 2500-5000 words and be accessible to a broad scientific audience.
Submission procedure
Before submitting, authors should read the AI&E submission guidelines at https://www.springer.com/journal/43681 in full. To submit, you should visit the online system at https://www.editorialmanager.com/aiet and create a new author account if you do not already have one. When creating your submission on the system, select the article type (e.g., Original Research, Review, or Opinion Paper), and then in the “Additional Information” section, answer “Yes” when asked if your manuscript belongs to a special issue, then select “T.C. : Trustworthy Adaptive and Learning Agents TALA”. If you do not mark your manuscript correctly as belonging to the TALA topical collection, it may not reach the correct editors.
DaSSWeb – Data Science and Statistics Webinar
Tuesday 13 July, 14:30
Speaker: Clara Cordeiro FCT, Universidade do Algarve and CEAUL
Title: WATER CHALLENGES
Zoom link: <videoconf-colibri.zoom.us/j/87373848710>videoconf-colibri.zoom.us/j/83875914782 <videoconf-colibri.zoom.us/j/87373848710>
Abstract: Water is one of the world’s most important natural resources. However, in recent years, periods of drought attributed to climate change have affected many countries worldwide. Consequently, this natural resource has become limited in some regions globally, such as the Algarve region in Portugal. Water utilities in the region have felt responsible for raising consumers’ awareness about responsible water use. In this context, water utilities want to promote sustainable water use and reduce water consumption through a water metering policy. However, when it comes to the processing of actual metering data, several difficulties arise. This seminar will show the challenges proposed by water utilities of this region and the strategies used to overcome them.
***********************************************************************
Acho que ficou um bom documento, nomeadamente porque refere amiúde as diferenças de riqueza entre países e entre pessoas que a IA fará aumentar.
Foi uma semana de discussão bem interessante, 6 horas por dia de zoom.
Abraços
Luís
——————————————————————————
Dear Participants and Observers,
We are pleased to share with you two documents:
The draft Recommendation on the Ethics of Artificial Intelligence (AI), approved in its entirety today Friday 25 June 2021, for the adoption by the 2nd Session of the Intergovernmental Meeting of Experts (category II) in November ;
The draft Final Report of the Rapporteur of the Intergovernmental Meeting of Experts, approved Friday 25 June 2021 .
Best regards,
The Bioethics and Ethics of Science and Technology Team in the Social and Human Science Sector
Estudo da Universidade de Stanford, divulgado no final de 2020, lista 15 sócios da APPIA entre os cientistas mais influentes do mundo
Em Outubro de 2020, foi publicado na revista PLOS Biology um artigo da autoria dos investigadores John Ioannidis, Kevin Boyack e Jeroen Baas, da Universidade de Stanford, no qual é realizada uma análise de métricas de citação padronizadas através das quais são identificados os 2% de autores/investigadores mais citados nas respectivas área de investigação, e que inclui 15 Sócios da APPIA.
O artigo, intitulado “Updated science-wide author databases of standardized citation indicators”, descreve a metodologia usada para processar o histórico de citações na plataforma Scopus desde os anos 90 do século XX até 2019, e através delas avaliar a influência/ impacto dos investigadores e instituições analisados.
Juntamente com o artigo, são disponibilizadas duas listas de cerca de 160,000 cientistas de 149 países e 22 áreas científicas distintas, uma medindo o impacto ao longo da carreira, e outra medindo o impacto no ano de 2019 apenas. Na lista de investigadores mais influentes ao longo da sua carreira podemos encontrar referências a diversos sócios da APPIA, nomeadamente:
Ana Paiva, Instituto Superior Técnico (sócia APPIA n. 164)
Arlindo Oliveira, Instituto Superior Técnico (sócio APPIA n. 487)
Bernardete Ribeiro, Universidade de Coimbra (sócia APPIA n. 642)
João Gama, Universidade do Porto (sócio APPIA n. 93)
João Marques-Silva, Centre National de la Recherche Scientifique (sócio APPIA n. 634)
Joel Rodrigues, Universidade da Beira Interior (sócio APPIA n. 399)
José Neves, Universidade do Minho (sócio APPIA n. 5)
Luís Caires, Universidade Nova de Lisboa (sócio APPIA n. 190)
Luís Camarinha-Matos, Universidade Nova de Lisboa (sócio APPIA n. 75)
Luís Moniz Pereira, Universidade Nova de Lisboa (sócio APPIA n. 1)
Paulo Cortez, Universidade do Minho (sócio APPIA n. 501)
Pedro Domingos, University of Washington (sócio APPIA n. 193)
Vladimiro Miranda, INESC-TEC (sócio APPIA n. 150)
Zita Vale, Instituto Politécnico do Porto (sócia APPIA n. 554)
Já na lista referente aos investigadores mais influentes de 2019, podemos encontrar referência aos sócios:
Ana Paiva, Instituto Superior Técnico (sócia APPIA n. 164)
Bernardete Ribeiro, Universidade de Coimbra (sócia APPIA n. 642)
Jaime Cardoso, Universidade do Porto (sócio APPIA n. 668)
João Gama, Universidade do Porto (sócio APPIA n. 93)
João Marques-Silva, Centre National de la Recherche Scientifique (sócio APPIA n. 634)
Joel Rodrigues, Universidade da Beira Interior (sócio APPIA n. 399)
José Neves, Universidade do Minho (sócio APPIA n. 5)
Luis Camarinha-Matos, Universidade Nova de Lisboa (sócio APPIA n. 75)
Paulo Cortez, Universidade do Minho (sócio APPIA n. 501)
Pedro Domingos, University of Washington (sócio APPIA n. 193)
Vladimiro Miranda, INESC-TEC (sócio APPIA n. 150)
Zita Vale, Instituto Politécnico do Porto (sócia APPIA n. 554)
A APPIA felicita todos os investigadores e sócios acima por este reconhecimento, e pelo trabalho que têm desenvolvido em prol da inteligência artificial em Portugal e no mundo.
DaSSWeb_ClaraCordeiro.pdf