[rede.APPIA] [CfP] Topical Collection on Trustworthy Adaptive and Learning Agents (AI and Ethics Journal)

Kind regards,

Patrick Mannion

Fernando P. Santos

Diederik M. Roijers

—

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.

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

Patrick Mannion (Lead Guest Editor), School of Computer Science, National University of Ireland Galway, webpage, email: patrick.mannion@nuigalway.ie 

Fernando P. Santos, University of Amsterdam, webpage, email: f.p.santos@uva.nl 

Diederik M. Roijers, Vrije Universiteit Brussel & HU University of Applied Sciences Utrecht, webpage, email: diederik.roijers@vub.be 

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.

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.

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.