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In this article, we present a design methodology for argumentation-based health information systems. With a focus on the application of formal argumentation, the methodology aims at eliciting requirements in regard to argumentation reasoning behavior, knowledge and user models, and business logic on levels below and above the argumentation layer. We highlight specific considerations that need to be made dependent on the system type, i.e., for clinical decision-support systems, patient-facing systems, and administration systems. In addition, we outline challenges in regards to the design of argumentation-based intelligent systems for healthcare, considering the state of the art of argumentation research, health information systems, and software design methods. For each challenge, we outline a mitigation strategy.

Intelligent systems are becoming increasingly complex and pervade a broad range of application domains, including safety-critical systems such as e-health, finance, and energy management. Traditional approaches are no longer capable of addressing the demand for trust and transparency in these applications. Hence, the current decade is demanding intelligent systems to be autonomous, and in particular explainable, transparent, and trustworthy. To satisfy such requirements, and therefore to comply with the recent EU regulations in the matter (e.g., GDPR), intelligent systems (e.g., Multi-Agent Systems - MAS) and technologies enabling tamper-proof and distributed consensus (e.g., Blockchain Technology - BCT) are conveying into reconciling solutions. Recently, the empowerment of MAS with BCT (and the use of BCT themselves) has gained considerable momentum, raising challenges, and unveiling opportunities. However, several ethical concerns have yet to be faced. This paper elaborates on the entanglement among ethical and technological challenges while proposing and discussing approaches that address these emerging research opportunities.

The so-called Internet of Things is of increasing importance for facilitating productivity across industries, i.e., by connecting sensors with manufacturing lines and IT system landscapes with an increasing degree of autonomy. In this context, a common challenge is enabling reasonable trade-offs between structure and control on the one hand and flexibility and human-like intelligent behavior on the other hand. To address this challenge, we establish the need for and requirements of a hybrid IoT-/agent-based business process orchestration architecture that utilizes open standards. We propose a four-layered architecture, which integrates autonomous agents and business process orchestration for IoT/agents, and provide a running example for a supply chain management (purchasing) use case. CCS CONCEPTS• Applied computing → Business process management; • Information systems; • Software and its engineering → Software as a service orchestration system

To cope with increasingly complex business, political, and economic environments, agent-based simulations (ABS) have been proposed for modeling complex systems such as human societies, transport systems, and markets. ABS enable experts to assess the influence of exogenous parameters (e.g., climate changes or stock market prices), as well as the impact of policies and their long-term consequences. Despite some successes, the use of ABS is hindered by a set of interrelated factors. First, ABS are mainly created and used by researchers and experts in academia and specialized consulting firms. Second, the results of ABS are typically not automatically integrated into the corresponding business process. Instead, the integration is undertaken by human users who are responsible for adjusting the implemented policy to take into account the results of the ABS. These limitations are exacerbated when the results of the ABS affect multi-party agreements (e.g., contracts) since this requires all involved actors to agree on the validity of the simulation, on how and when to take its results into account, and on how to split the losses/gains caused by these changes. To address these challenges, this paper explores the integration of ABS into enterprise application landscapes. In particular, we present an architecture that integrates ABS into cross-organizational enterprise resource planning (ERP) processes. As part of this, we propose a multi-agent systems simulator for the Hyperledger blockchain and describe an example supply chain management scenario type to illustrate the approach.

International audience; The continuous integration of software-intensive systems together with the ever-increasing computing power offer a breeding ground for intelligent agents and multi-agent systems (MAS) more than ever before. Over the past two decades, a wide variety of languages, models, techniques and methodologies have been proposed to engineer agents and MAS. Despite this substantial body of knowledge and expertise, the systematic engineering of large-scale and open MAS still poses many challenges. Researchers and engineers still face fundamental questions regarding theories, architectures, languages, processes, and platforms for designing, implementing, running, maintaining, and evolving MAS. This paper reports on the results of the 6th International Workshop on Engineering Multi-Agent Systems (EMAS 2018, 14th-15th of July, 2018, Stockholm, Sweden), where participants discussed the issues above focusing on the state of affairs and the road ahead for researchers and engineers in this area.

Executing business processes in a decentralized manner can improve inter-organizational efficacy. For example, blockchain-based process execution allows, at least conceptually, for cross-organizational compatibility, data integration, and integrity assurance without the need for a centralized trusted operator. However, most business processes run in agile and rapidly changing business environments. Updating a decentralized process requires continuous and extensive consensus-building efforts. Reflecting all organizations' business requirements is hardly practicable. Hence, in many real-life scenarios, to support cases with initially unforeseen properties, organizations can allow to bypass the decentralized process and fall-back to local variants. Yet, the decision to bypass or update a given process can have significant social implications since it may encourage a social dynamic that encourages collective avoidance of the decentralized process. This paper proposes a multi-agent simulation system to assess the social consequences of approving a bypass under given conditions. The proposed simulation is intended to inform the decision-maker (human or machine) on whether to allow to bypass a process or not. Moreover, we present an architecture for the integration of multi-agent simulation system, local process engine, and decentralized process execution environment, and describe a possible implementation with a particular tool chain.

In a previous publication, we introduced the core concepts of empathic agents as agents that use a combination of utility-based and rule-based approaches to resolve conflicts when interacting with other agents in their environment. In this work, we implement proof-of-concept prototypes of empathic agents with the multi-agent systems development framework Jason and apply argumentation theory to extend the previously introduced concepts to account for inconsistencies between the beliefs of different agents. We then analyze the feasibility of different admissible set-based argumentation semantics to resolve these inconsistencies. As a result of the analysis, we identify the maximal ideal extension as the most feasible argumentation semantics for the problem in focus.

Information systems execute increasingly complex business processes, often across organizations. Blockchain technology has emerged as a potential facilitator of (semi)-autonomous cross-organizational business process execution, in particular, so-called consortium blockchains can be considered as promising enablers in this context, as they do not require the use of cryptocurrency-based blockchain technology, as long as the trusted (authenticated) members of the network are willing to provide computing resources for consensus-finding. However, increased autonomy in the execution of business processes also requires the delegation of business decisions to machines. To support complex decision-making processes by assessing potential future outcomes, agent-based simulations can be considered a useful tool for the autonomous enterprise. In this paper, we explore the intersection of multi-agent simulations and consortium blockchain technology in the context of enterprise applications by devising architectures and technology stacks for both off-chain and on-chain agent-based simulation in the context of blockchain-based business process execution.