Separation of Concerns for Mechatronic Multi-agent Systems Through Dynamic Communities

Klein, Florian; Giese, Holger

doi:10.1007/978-3-540-31846-0_16

Cited by 9 publications

(5 citation statements)

References 15 publications

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“…In order to achieve the desired properties, we now extend the specification with social structures controlling the architectural evolution and the real-time coordination, prominently using Mechatronic UML coordination patterns [13]. As a means of structuring the problem domain, we define a hierarchy of cultures [17], each of which is responsible for ensuring a set of specific system properties.…”

Section: Modelingmentioning

confidence: 99%

Symbolic invariant verification for systems with dynamic structural adaptation

Becker

Beyer

Giese

et al. 2006

Proceedings of the 28th International Conference on Software Engineering

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112

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The next generation of networked mechatronic systems will be characterized by complex coordination and structural adaptation at run-time. Crucial safety properties have to be guaranteed for all potential structural configurations. Testing cannot provide safety guarantees, while current model checking and theorem proving techniques do not scale for such systems. We present a verification technique for arbitrarily large multi-agent systems from the mechatronic domain, featuring complex coordination and structural adaptation. We overcome the limitations of existing techniques by exploiting the local character of structural safety properties. The system state is modeled as a graph, system transitions are modeled as rule applications in a graph transformation system, and safety properties of the system are encoded as inductive invariants (permitting the verification of infinite state systems). We developed a symbolic verification procedure that allows us to perform the computation on an efficient BDD-based graph manipulation engine, and we report performance results for several examples.

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Section: Modelingmentioning

confidence: 99%

Symbolic invariant verification for systems with dynamic structural adaptation

Becker

Beyer

Giese

et al. 2006

Proceedings of the 28th International Conference on Software Engineering

Self Cite

112

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“…The study of emergence spans many domains including economics [39], biology [40], sociology [41], mechatronics [42], nanotechnology [43], spatial computing [44], philosophy [45] etc.…”

Section: Stigmergymentioning

confidence: 99%

Complex Adaptive Blockchain Governance

Thomas

Mantri

2018

MATEC Web Conf.

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The blockchain revolution upholds the decentralizing ideal of “control nothing.” It is natural that such a pursuit would face issues of governance that demand reasonable control; control that is both operational as well as adaptive in nature. Eliminating middlemen and handing over controls to a trusted system of trustless agents does not thereby bestow trust across time. This is especially true when relentless change is the order of the day. Issues of governance rise up when blockchain systems (especially those that have embedded smart contracts) are forced to operate increasingly away from their original intent. Smart contracts need governance when beset with the problem of the unknown-unknowns. Guided by the axiomatic approach, this paper looks at the paradoxical issue of blockchain governance from a Complex Adaptive Systems (CAS) perspective that helps frame the fundamental problem of decentralization. The objective is to solve the Blockchain Governance Kernel Design. Real-life examples are used to illustrate the findings.

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“…The two key concepts for dealing with context on the Conceptual Level are Cultures and Communities, introduced in [14,10]. A Culture defines a set of Roles, prescribed Behaviors expressed by coordination patterns or transformation rules, rules for determining membership and Norms for interpreting messages and displayed behavior that ascribe certain Professed Intentions to them.…”

Section: Social Environmentmentioning

confidence: 99%

“…One particular relationship, dynamically committing to Roles, is an important abstraction for characterizing adaptive agent behavior, as proposed by [13]. Social Context is usually induced by the composition of several Communities; in fact, we have proposed using Communities as architectural views for modeling non-orthogonal concerns [14].…”

Section: Social Contextmentioning

confidence: 99%

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Analysis and design of physical and social contexts in multi-agent systems using UML

KleinFlorian

GieseHolger

2005

SIGSOFT Softw. Eng. Notes

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Multi-agent technology promises to provide the ability to adapt to changing external contexts. To tap this potential, context needs to play a central role in the analysis and design of multi-agent systems. In this paper, a pragmatic approach to the classification and modeling of the relevant contexts is presented, focusing on a useful operational description rather than epistemological correctness. We then show how our approach supports the analysis and design of physical and social contexts for embedded multi-agent systems using the UML, providing a number of different examples.

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Separation of Concerns for Mechatronic Multi-agent Systems Through Dynamic Communities

Cited by 9 publications

References 15 publications

Symbolic invariant verification for systems with dynamic structural adaptation

Symbolic invariant verification for systems with dynamic structural adaptation

Complex Adaptive Blockchain Governance

Analysis and design of physical and social contexts in multi-agent systems using UML

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