Edit Event: EMAS 2020

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==Call for Papers== Despite the substantial body of knowledge and expertise developed in the design and development of multi-agent systems (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, validate and evolve MAS? * Which architectures are most suitable for MAS of different domains? * How to seamlessly integrate MAS engineering with mainstream engineering models, languages, frameworks and tools? * How to seamlessly integrate AI and machine learning techniques into design/programming languages and tools for agent-based systems? * How to enable agent-based systems to deal with continuous change, for example in the operating environment or user requirements? * What are the implications of MAS engineering in the context of continuous development and deployment? * How to ensure and control global behaviour of decentralised, open and large-scale MAS? * How to express the requirements for large-scale and open MAS and how to translate these requirements into agent goals? * How to scale with the complexity of real-world application domains? * How can MAS help developing Cyber-Physical Systems and Internet-of-Things? Which development tools and frameworks are available/needed? * Which processes and methodologies can integrate the above and provide a disciplined approach to rapid yet high-quality development of MAS? * How to engineer agent and multi-agent systems that are secure and protect the privacy concerns of users? ==Topics== The topics include but are not limited to: Programming frameworks, languages, models and abstractions for all aspects of MAS cognitive models and architectures, such as BDI agent-oriented programming concepts and abstractions patterns and idioms for agent-oriented programming social, organizational and normative aspects agent coordination agent communication, trust, commitments and reputation contracts, negotiation policies mobile agents learning agents applying agent-oriented programming to real-world applications Formal methods and declarative technologies for specification, verification, and engineering of MAS semantics for multi-agent programming languages modal and epistemic logics for agent modeling game theory and mechanism design for multi-agent systems semantics of agent communication (constraint) logic programming approaches to agent systems distributed constraint satisfaction declarative approaches to engineering agent-based systems high-level executable multi-agent specification languages algorithms for MAS programming (e.g., coordination, cooperation, negotiation) verification of MAS with machine learning components MAS software engineering methodologies and techniques, and development concerns software architectures for multi-agent systems qualities and tradeoffs of agent-based architectures goal-oriented designreusable design knowledge: patterns and reference architectures modeling languages for agents and MAS testing of agent-based software fault tolerance and load balancing for mobile MAS safety and security for mobile MAS deployment autonomy vs. dependability and robustness security and trust in multi-agent systems Interoperability and integration interoperability and standards for MAS standardization efforts for multi-agent systems integration of multi-agent and mainstream technologies integration of agents with legacy systems middleware integration of agent-based software implications of introducing agent-based solutions on the development organization Tools and testbeds benchmarks and testbeds for comparing multi-agent programming languages and tools CASE tools to support agent-oriented software development in practice agent/environment/interaction/organization development tools and platforms generic tools and infrastructures for multi-agent programming coordination infrastructures for multi-agent systems Using MAS techniques for engineering self-organizing or self-adaptive systems systems of systems engineering service-oriented computing and semantic web multi-agent based simulation social engineering concurrent and distributed systems grid computing pervasive computing cloud and edge computing cyber-physical systems big data applications internet of things Empirical studies and (industrial) experience reports on engineering MAS applications e-health e-commerce e-learning socio-technical systems social networks (human-)robot systems ==Submission Instructions== We solicit four types of submission: * 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 either (a) describe novel and promising ideas and/or techniques that are in an early stage of development; or (b) 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. To that end, short papers will be reviewed under specific review guidelines (8 pages (excluding references) in LNCS format). * Doctoral project papers should describe a research effort of an MSc student or the dissertation research of a PhD student in the field of engineering multi-agent systems. The paper should clearly describe the problem tackled, a justification why this problem is important, the research method, the (expected) contributions of the research, and the evaluation. This paper can be co-authored by the student and their supervisor(s) only (6 pages (excluding references) in LNCS format). * Tool, testbeds and demo papers should describe a novel tool or demonstration in the field of engineering multi-agent systems. Submission may range from early prototypes to in-house or pre-commercialised products. Authors of other EMAS 2020 papers are also welcomed 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 link (4 pages (excluding references) in LNCS format). 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/conferences/?conf=emas2020. When you enter the title of your paper in the data section in EasyChair, you must add as the first word the category to which the paper has been submitted (this first word does not need to be included in the submitted paper): * REGULAR for regular papers (16 pages (excluding references)) * SHORT for short papers (8 pages (excluding references)) Note: The paper's introduction must make it clear whether the paper is early stage results (a) or a vision paper (b). * DOCTORAL for doctoral project papers (6 pages (excluding references)) * DEMO for tools, testbeds, and demo papers (4 pages (excluding references)) Authors of accepted papers will be invited to submit revised and extended versions of the EMAS papers for inclusion in the post-proceedings that we will be published as a volume in Springer's Lecture Notes in Artificial Intelligence. Important Dates Submission deadline: 28 Feb, 2020 Notification: 10 March, 2020 Camera-ready deadline: 1 April 7 April, 2020 EMAS: 9-10 8-9 May, 2020

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