Autonomy in Software Systems

Timm, Ingo J.; Knirsch, Peter; Kreowski, Hans‐Jörg; Timm‐Giel, Andreas

doi:10.1007/978-3-540-47450-0_17

Cited by 7 publications

(7 citation statements)

References 14 publications

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“…Die Implementierung von intelligenten, autonomen Systemen in der logistischen Praxis erfordert Technologien wie RFID, Embedded Systems oder Wearable/Mobile Computing. Bei der Gestaltung von solchen Systemen werden unterschiedliche Formen der Autonomie genutzt, die sich entweder auf die autonome Realisierung der operativen, der taktischen oder der strategischen Planung und Ausführung [23] beziehen. Die Interaktion von autonomen Systemen soll im Idealfall zu einer Optimierung eines Globalsystems bei lokaler Optimierung der Zielsysteme führen.…”

Section: Informatikmethoden Und Iuk-technologienunclassified

Künstliche Intelligenz in der Logistik

Timm

Lattner

2010

Künstl Intell

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Section: Informatikmethoden Und Iuk-technologienunclassified

Künstliche Intelligenz in der Logistik

Timm

Lattner

2010

Künstl Intell

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“…These approaches are closely related to our approach because of the special features inherent to agents such as autonomy or reactivity (cf. [16] where autonomous units are related to the VSK model of multi-agent systems, see e.g., [17]). …”

Section: Related Workmentioning

confidence: 99%

Communities of Autonomous Units for Pickup and Delivery Vehicle Routing

Kreowski

Kuske

2008

Applications of Graph Transformations With Industrial Relevance

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Abstract. Communities of autonomous units are being developed for formal specification and semantic analysis of systems of interacting and mobile components. The autonomous units of a community are rulebased, self-controlled, goal-driven, and operate and move in a common environment. We employ communities of autonomous units to model the dynamic pickup and delivery problem with the general idea to demonstrate their suitability for a range of logistic tasks.

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“…Various approaches on coordination and implementation of information exchange as well as process and workflow execution by information systems have been developed as part of enterprise resource planning and logistics management systems. To increase efficiency and effectivity of production in a globalized world, innovative approaches propose decentralization and autonomy [1,2,3]. Thus, information exchange, workflow specification and implementation of workflows by information systems has been in focus of early approaches to enterprise resource planning and logistics management systems.…”

Section: Introductionmentioning

confidence: 99%

“…The following formalization of an agent Ag is based on logics and concepts from[40,41,42]. Moreover, the actual definitions are derived from[20,1].The see and execute functions of an agent are interfaces to its environment (see Definition 4.3). The intentional forgetting mechanism, i.e., a shift in the capability configuration of an agent, is implemented in an agent's ref lect function.It allows for a reconfiguration of an agents local state.Definition 4.1.…”

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confidence: 99%

Analyzing the Effects of Role Configuration in Logistics Processes using Multiagent-Based Simulation: An Interdisciplinary Approach

Timm¹,

Reuter²,

Ulfert³

et al. 2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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Current trends like the digital transformation and Industry 4.0 are challenging logistics management: flexible process development and optimization has been a primary concern in research in the last two decades. However, flexibility is limited by its underlying distribution of action and task knowledge. Thus, our objective is to develop an approach to optimize performance of logistics processes by dynamic (re-) configuration of knowledge in teams. One of the key assumptions for that approach is, that the distribution of knowledge has impact on team's performance. Consequently, we propose a formal specification for representing active resources (humans or smart machines) and distribution of action knowledge in multiagent-based simulation. In the second part of this paper, we analyze process quality in a psychologically validated laboratory case study. Our simulation results support our assumption, i.e., the results show that there is significant influence of knowledge distribution on process quality.

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Autonomy in Software Systems

Cited by 7 publications

References 14 publications

Künstliche Intelligenz in der Logistik

Künstliche Intelligenz in der Logistik

Communities of Autonomous Units for Pickup and Delivery Vehicle Routing

Analyzing the Effects of Role Configuration in Logistics Processes using Multiagent-Based Simulation: An Interdisciplinary Approach

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