1,721,430 research outputs found
Environment as a First-class Abstraction in Multi-Agent Systems
Full text linkThe current practice in multiagent systems typically associates the environment with resources that are external to agents and their communication infrastructure. Advanced uses of the environment include infrastructures for indirect coordination, such as digital pheromones, or support for governed interaction in electronic institutions. Yet, in general, the notion of environment is not well defined. Functionalities of the environment are often dealt with implicitly or in an ad-hoc manner. This is not only poor engineering practice, it also hinders engineers to exploit the full potential of the environment in multiagent systems.
In this paper, we put forward the environment as an explicit part of multiagent systems.We give a definition stating that the environment in a multiagent system is a first-order abstraction with dual roles: (1) the environment provides the surrounding conditions for agent to exists, which implies that the environment is an essential part of every multiagent system, and (2) the environment provides an exploitable design abstraction for building multiagent system applications. We discuss the responsibilities of such an environment in multiagent systems and we present a reference model for the environment that can serve as a basis for environment engineering. To illustrate the power of the environment as a design abstraction, we show how the environment is successfully exploited in a real world application. Considering the environment as a first-order abstraction in multiagent systems opens up new horizons for research and development in multiagent systems
A reference architecture for situated multiagent systems
Full text linkA reference architecture integrates a set of architectural patterns that have proven their value for a family of applications. Such family of applications is characterized by specific functionality and quality requirements. A reference architecture provides a blueprint for developing software architectures for applications that share that common base. As such, a reference architecture provides a means for large-scale reuse of architectural design. This paper gives an overview of a reference architecture for situated multiagent systems we have developed in our research. We discuss various architectural views of the reference architecture. Per view, we zoom in on the main view packets, each of them containing a bundle of information of a part of the reference architecture. For each view packet we explain the rationale for the design choices that were made and we give built-in mechanisms that describe how the view packet can be exercised to build a concrete software architecture. We illustrate the use of the reference architecture with an excerpt of the software architecture of an industrial AGV transportation system. © Springer-Verlag Berlin Heidelberg 2007.sponsorship: Future University, Hakodate, Japanstatus: Publishe
On the role of software architecture for simulating multi-agent systems
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A middleware model in alloy for supply chain-wide agent interactions
No full textTo support the complex coordination activities involved in supply chain management, more and more companies have autonomous software agents acting on their behalf. Due to confidentiality concerns, such as hiding sensitive information from competitors, agents typically only have a local view on the supply chain. In many situations, however, companies would like to expand the view of their agents to share valuable information such as transportation tracking and service delays. Non of the participating companies, however, has enough knowledge or authority to realize such interactions in a controlled manner. In this paper, we present an organization middleware that offers a collaboration platform and enables agents to interact across the boundary of local interactions. Policies and laws enable companies to define the scope of interactions of their agents and the restrictions on their exposed information. Using Alloy, we formally define the relation between the interactions offered by the middleware, the exposed information and the provided policies and laws. This allows us to guarantee a number properties which are of particular interest to companies using the middleware
Self-Adaptation for Cyber-Physical Systems: A Systematic Literature Review
No full text© 2016 ACM. Context: Cyber-physical systems (CPS) seamlessly integrate computational and physical components. Adaptability, realized through feedback loops, is a key requirement to deal with uncertain operating conditions in CPS. Objective: We aim at assessing state-of-art approaches to handle self-adaptation in CPS at the architectural level. Method: We conducted a systematic literature review by searching four major scientific data bases, resulting in 1103 candidate studies and eventually retaining 42 primary studies included for data collection after applying inclusion and exclusion criteria. Results: The primary concerns of adaptation in CPS are performance, flexibility, and reliability. 64% of the studies apply adaptation at the application layer and 24% at the middleware layer. MAPE (Monitor-Analyze-Plan-Execute) is the dominant adaptation mechanism (60%), followed by agents and self-organization (both 29%). Remarkably, 36% of the studies combine different mechanisms to realize adaptation; 17% combine MAPE with agents. The dominating application domain is energy (24%). Conclusions: Our findings show that adaptation in CPS is a cross-layer concern, where solutions combine different adaptation mechanisms within and across layers. This raises challenges for future research both in the field of CPS and self-adaptation, including: how to map concerns to layers and adaptation mechanisms, how to coordinate adaptation mechanisms within and across layers, and how to ensure system-wide consistency of adaptation.status: Publishe
Patterns for Self-Adaptation in Cyber-Physical Systems
No full text© Springer International Publishing AG 2017. Engineering Cyber-Physical Systems (CPS) is challenging, as these systems have to handle uncertainty and change during operation. A typical approach to deal with uncertainty is enhancing the system with self-adaptation capabilities. However, realizing self-adaptation in CPS, and consequently also in Cyber-Physical Production Systems (CPPS) as a member of the CPS family, is particularly challenging due to the specific characteristics of these systems, including the seamless integration of computational and physical components, the inherent heterogeneity and large-scale of such systems, and their open-endedness. In this chapter we survey CPS studies that apply the promising design strategy of combining different self-adaptation mechanisms across the technology stack of the system. Based on the survey results, we derive recurring adaptation patterns that structure and consolidate design knowledge. The patterns offer problem-solution pairs to engineers for the design of future CPS and CPPS with self-adaptation capabilities. Finally, the chapter outlines the potential of collective intelligence systems for CPPS and their engineering based on the survey results.status: Accepte
Uncertainty in Self-adaptive Systems:A Research Community Perspective
Full text linkOne of the primary drivers for self-adaptation is ensuring that systems achieve their goals regardless of the uncertainties they face during operation. Nevertheless, the concept of uncertainty in self-adaptive systems is still insufficiently understood. Several taxonomies of uncertainty have been proposed, and a substantial body of work exists on methods to tame uncertainty. Yet, these taxonomies and methods do not fully convey the research community’s perception on what constitutes uncertainty in self-adaptive systems and on the key characteristics of the approaches needed to tackle uncertainty. To understand this perception and learn from it, we conducted a survey comprising two complementary stages in which we collected the views of 54 and 51 participants, respectively. In the first stage, we focused on current research and development, exploring how the concept of uncertainty is understood in the community and how uncertainty is currently handled in the engineering of self-adaptive systems. In the second stage, we focused on directions for future research to identify potential approaches to dealing with unanticipated changes and other open challenges in handling uncertainty in self-adaptive systems. The key findings of the first stage are: (a) an overview of uncertainty sources considered in self-adaptive systems, (b) an overview of existing methods used to tackle uncertainty in concrete applications, (c) insights into the impact of uncertainty on non-functional requirements, (d) insights into different opinions in the perception of uncertainty within the community and the need for standardised uncertainty-handling processes to facilitate uncertainty management in self-adaptive systems. The key findings of the second stage are: (a) the insight that over 70% of the participants believe that self-adaptive systems can be engineered to cope with unanticipated change, (b) a set of potential approaches for dealing with unanticipated change, (c) a set of open challenges in mitigating uncertainty in self-adaptive systems, in particular in those with safety-critical requirements. From these findings, we outline an initial reference process to manage uncertainty in self-adaptive systems. We anticipate that the insights on uncertainty obtained from the community and our proposed reference process will inspire valuable future research on self-adaptive systems.sponsorship: Danny Weyns' work was supported by the projects "Trustworthy Decentralized Self-Adaptive Systems" (C14/18/066) and "Dependable Adaptive Software Systems for the Digital World" (ISPLI/18/019). Radu Calinescu's work was funded by the UKRI project EP/V026747/1 Trustworthy Autonomous Systems Node in Resilience and the Assuring Autonomy Interational Programme. (project "Trustworthy Decentralized Self-Adaptive Systems"|C14/18/066, project "Dependable Adaptive Software Systems for the Digital World"|ISPLI/18/019, UKRI project|EP/V026747/1, SPF|EP/V026747/1)status: Publishe
Big Data from the Cloud to the Edge: The aggregate computing solution (Position Paper)
No full textWe advocate a novel concept of dependable intelligent edge systems
(DIES) i.e., the edge systems ensuring a high degree of dependability
(e.g., security, safety, and robustness) and autonomy because of their
applications in critical domains. Building DIES entail a paradigm
shift in architectures for acquiring, storing, and processing potentially large amounts of complex data: data management is placed
at the edge between the data sources and local processing entities,
with loose coupling to storage and processing services located in
the cloud. As such, the literal definition of edge and intelligence is
adopted, i.e., the ability to acquire and apply knowledge and skills
is shifted towards the edge of the network, outside the cloud infrastructure. This paradigm shift offers flexibility, auto configuration, and auto diagnosis, but also introduces novel challenges
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