Call for Papers

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A key unifying theme underlying Artificial Intelligence and Machine Learning is the idea of intelligent software agents able to reason, act, interact, and learn. This metaphor has stimulated much research in AI and particularly in Autonomous Agents and Multi-Agent Systems, giving rise to research in agent-oriented software engineering, programming multi-agent systems, and declarative agent languages and technologies.

Despite the substantial body of knowledge and expertise developed in the design and development of MAS, the systematic development of large-scale and open MAS still poses many challenges. Even though various languages, models, techniques, and methodologies have been proposed in the literature, researchers and developers are still faced with fundamental questions attaining MAS engineering, such as:

• How to specify, design, implement, verify, test, and validate large-scale and open MAS?
• How to ensure and control the global behaviour of decentralised, large-scale, and open MAS?
• How to seamlessly integrate AI, machine learning, and data-driven techniques into the design and development of agent-based systems?
• Which (multi-)agent architectures and languages are most suitable for MAS in different domains?
• How to engineer agent and multi-agent systems that are secure and protect the privacy concerns of users?
• How to scale to the complexity of real-world application domains?
• What are the implications of MAS engineering in the context of continuous development and deployment?
• How can MAS be applied in specific application areas, such as Cyber-Physical Systems and Internet of Things / Web of Things?
• How to seamlessly integrate MAS engineering with mainstream software engineering models, languages, frameworks and tools?
• Which processes and methodologies can integrate the above and provide a disciplined approach to the engineering of MAS?

EMAS 2023 will provide a forum for researchers and practitioners interested in the theory and practice of engineering intelligent agents and multi-agent systems (MAS). The overall purpose of the workshop is to facilitate the cross-fertilization of ideas and experiences in the various fields to:

• enhance our knowledge of the theory and practice of engineering intelligent agents and multi-agent systems, and advance the state of the art;
• demonstrate how MAS methodologies, architectures, languages, and tools can be used in the engineering of deployed large-scale, open, and data-driven MAS;
• define new directions for engineering MAS by drawing on results and recommendations from related research areas; and
• encourage Ph.D. and Master’s students to become involved in and contribute to the area.

Topics

Topics of interest include but are not limited to:

• Traditional MAS engineering topics, including requirements and formal specifications; architecture and modeling; verification and validation; programming and languages; testing; maintenance and evolution.
• MAS engineering for conventional AI techniques, including machine learning-based abstractions and data-driven approaches.
• MAS engineering for novel technologies, including IoT/WoT, hypermedia services, microservices, serverless computing, blockchain.
• MAS engineering abstractions, including norms, emotions, protocols, BDI, and goals.
• MAS engineering for application domains, including business, health, finance, mobility and transportation.
• MAS engineering for sociotechnical systems, including ethics, laws and regulations, governance, responsibility and accountability.
• MAS engineering surveys.

Important Dates

Submission deadline:	February 22, 2023 March 5, 2023
Author notification:	March 27, 2023
Camera-ready deadline	April 27, 2023
EMAS	May 29-30, 2023

Submissions

We solicit four types of submissions:

• Regular papers should: (1) clearly describe innovative and original research; or (2) report a survey on a research topic in the field; or (3) explain how existing techniques have been applied to a real-world case. (16 pages, excluding references, in LNCS format).
• Short papers should: (1) describe novel and promising ideas and/or techniques that are in an early stage of development; or (2) present a vision for some part of the field, including challenges, and research opportunities (see the AAMAS Blue Sky Track CFP for more information on these sort of papers). (8 pages, excluding references, in LNCS format).
• Student papers should describe M.Sc. or Ph.D. research in the field of engineering multi-agent systems. The paper should clearly describe the problem tackled and why it is important, the research method, the (expected) contributions of the research, and the evaluation. The lead author on the paper should be the student. (6 pages, excluding references, in LNCS format).
• Tools, testbeds, and demo papers should describe a novel tool or demonstration in the field of engineering multi-agent systems. Submissions may range from early prototypes to in-house or pre-commercialised products. Authors of other EMAS 2023 papers are also welcome to submit an accompanying tool/demo paper. The paper should provide a link to supplementary material that allows the reviewers to evaluate the submission such as website or movie (4 pages, excluding references, in LNCS format).

Student paper award: We encourage students to submit to EMAS 2023. Papers where the main author is a student should be identified as such and will be eligible for the best student paper award.

Submission policy: all papers should be original and not be submitted elsewhere. The review process is single blind: submissions should not be blind, reviewers will be.

The LNCS formatting style is available via: http://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines

The EasyChair submission page can be found here: https://easychair.org/my/conference?conf=emas2023

Authors of accepted papers will be invited to submit revised and extended versions of the EMAS papers for inclusion in the post-proceedings that will be published as a volume in Springer's Lecture Notes in Artificial Intelligence (LNAI).