Viewpoint Development of Stochastic Hybrid Systems

Nowadays, due to the explosive spreading of networked and highly distributed systems, mastering system complexity becomes a critical issue. Two development and verification paradigms have become more popular: viewpoints and randomisation. The viewpoints offer large freedom and introduce concurrency and compositionality in the development process. Randomisation is now a traditional method for reducing complexity (comparing with deterministic models) and it offers finer analytical analysis tools (quantification over non-determinism, multi-valued logics, etc). In this paper, we propose a combination of these two paradigms introducing a viewpoint methodology for systems with stochastic behaviours

An investigation into modelling approaches for industrial symbiosis: a literature review

The aim of this paper is to understand how to model industrial symbiosis networks in order to favour its implementation and provide a framework to guide companies and policy makers towards it. Industrial symbiosis is a clear example of complex adaptive systems and traditional approaches (i.e., Input/Output analysis, Material flow analysis) are not capable to capture these dynamics behaviours. Therefore, the aim of this literature review is to investigate: i) the most used modelling and simulation approaches to analyse industrial symbiosis and ii) their characteristics in terms of simulation methods, interaction mechanisms and simulations software. Findings from our research suggest that a hybrid modelling and simulation approach, based on agent-based and system dynamics, could be an appropriate method for industrial symbiosis analysis and design

Towards adaptive multi-robot systems: self-organization and self-adaptation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible

Discrete Simulation of Behavioural Hybrid Process Calculus

Hybrid systems combine continuous-time and discrete behaviours. Simulation is one of the tools to obtain insight in dynamical systems behaviour. Simulation results provide information on performance of system and are helpful in detecting potential weaknesses and errors. Moreover, the results are handy in choosing adequate control strategies and parameters. In our contribution we report a work in progress, a technique for simulation of Behavioural Hybrid Process Calculus, an extension of process algebra that is suitable for the modelling and analysis of hybrid systems

On Properties of Policy-Based Specifications

The advent of large-scale, complex computing systems has dramatically increased the difficulties of securing accesses to systems' resources. To ensure confidentiality and integrity, the exploitation of access control mechanisms has thus become a crucial issue in the design of modern computing systems. Among the different access control approaches proposed in the last decades, the policy-based one permits to capture, by resorting to the concept of attribute, all systems' security-relevant information and to be, at the same time, sufficiently flexible and expressive to represent the other approaches. In this paper, we move a step further to understand the effectiveness of policy-based specifications by studying how they permit to enforce traditional security properties. To support system designers in developing and maintaining policy-based specifications, we formalise also some relevant properties regarding the structure of policies. By means of a case study from the banking domain, we present real instances of such properties and outline an approach towards their automatised verification.Comment: In Proceedings WWV 2015, arXiv:1508.0338

Unlocking medical leadership’s potential:a multilevel virtuous circle?

Background and aim: Medical leadership (ML) has been introduced in many countries, promising to support healthcare services improvement and help further system reform through effective leadership behaviours. Despite some evidence of its success, such lofty promises remain unfulfilled. Method: Couched in extant international literature, this paper provides a conceptual framework to analyse ML's potential in the context of healthcare's complex, multifaceted setting. Results: We identify four interrelated levels of analysis, or domains, that influence ML's potential to transform healthcare delivery. These are the healthcare ecosystem domain, the professional domain, the organisational domain and the individual doctor domain. We discuss the tensions between the various actors working in and across these domains and argue that greater multilevel and multistakeholder collaborative working in healthcare is necessary to reprofessionalise and transform healthcare ecosystems

Constructing living buildings: a review of relevant technologies for a novel application of biohybrid robotics

Biohybrid robotics takes an engineering approach to the expansion and exploitation of biological behaviours for application to automated tasks. Here, we identify the construction of living buildings and infrastructure as a high-potential application domain for biohybrid robotics, and review technological advances relevant to its future development. Construction, civil infrastructure maintenance and building occupancy in the last decades have comprised a major portion of economic production, energy consumption and carbon emissions. Integrating biological organisms into automated construction tasks and permanent building components therefore has high potential for impact. Live materials can provide several advantages over standard synthetic construction materials, including self-repair of damage, increase rather than degradation of structural performance over time, resilience to corrosive environments, support of biodiversity, and mitigation of urban heat islands. Here, we review relevant technologies, which are currently disparate. They span robotics, self-organizing systems, artificial life, construction automation, structural engineering, architecture, bioengineering, biomaterials, and molecular and cellular biology. In these disciplines, developments relevant to biohybrid construction and living buildings are in the early stages, and typically are not exchanged between disciplines. We, therefore, consider this review useful to the future development of biohybrid engineering for this highly interdisciplinary application.publishe

Multi-level agent-based modeling - A literature survey

During last decade, multi-level agent-based modeling has received significant and dramatically increasing interest. In this article we present a comprehensive and structured review of literature on the subject. We present the main theoretical contributions and application domains of this concept, with an emphasis on social, flow, biological and biomedical models.Comment: v2. Ref 102 added. v3-4 Many refs and text added v5-6 bibliographic statistics updated. v7 Change of the name of the paper to reflect what it became, many refs and text added, bibliographic statistics update

Investigation of sequence processing: A cognitive and computational neuroscience perspective

Serial order processing or sequence processing underlies many human activities such as speech, language, skill learning, planning, problem-solving, etc. Investigating the neural bases of sequence processing enables us to understand serial order in cognition and also helps in building intelligent devices. In this article, we review various cognitive issues related to sequence processing with examples. Experimental results that give evidence for the involvement of various brain areas will be described. Finally, a theoretical approach based on statistical models and reinforcement learning paradigm is presented. These theoretical ideas are useful for studying sequence learning in a principled way. This article also suggests a two-way process diagram integrating experimentation (cognitive neuroscience) and theory/ computational modelling (computational neuroscience). This integrated framework is useful not only in the present study of serial order, but also for understanding many cognitive processes