Following the Problem Organisation: A Design Strategy for Engineering Emergence

Noël, Victor; Zambonelli, Franco

doi:10.1007/978-3-319-10422-5_33

Cited by 2 publications

(1 citation statement)

References 9 publications

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“…Agents have a partial view of the environment, they act jointly to produce a result for a goal that cannot be achieved individually. Due to the distribution of tasks within the agents composing a MAS and the possibility to decentralize control and decision, MAS are more suitable to model and simulate complex systems than traditional approaches [8]. MAS offer a framework to model, study, and control complex systems with a bottom-up approach by focusing on the entities and their interactions to solve a wide variety of problems [9].…”

Section: Introductionmentioning

confidence: 99%

A Cooperative Multi-Agent System for Crowd Sensing Based Estimation in Smart Cities

2020

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The concept of Smart City has spread as a solution to ensure better access to information and services to citizens, but also as a means to reduce the environmental footprint of cities. To this end, a continuous and wide observation of the environment is necessary to analyze information that enables government bodies to act on the environment appropriately. Moreover, a diffused acquisition of information requires adequate infrastructure and proper devices, which results in relevant installation and maintenance costs. Our proposal enables reducing the number of necessary sensors to be deployed while ensuring that information is available at any time and anywhere. We present the HybridIoT system to cope with the lack of environmental information in the urban context through an estimation technique that integrates heterogeneous data acquired from some different sensors. HybridIoT can be deployed in large-scale contexts and ensures data accessibility even if devices enter or leave the system at any time and everywhere. We compare the results to those obtained by state-of-the-art techniques to assess the validity of our proposal, in particular concerning the properties of openness, large-scale, and heterogeneity, of primary importance in the context of the development of systems to be deployed in the smart city context.

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Section: Introductionmentioning

confidence: 99%

A Cooperative Multi-Agent System for Crowd Sensing Based Estimation in Smart Cities

2020

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Researching Adaptive Systems with RRobots

Phillips

Blackburn

2015

Procedia Computer Science

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This research effort proposes a framework for conducting simulation-based research experiments using a pre-existing system. RRobots is a simulation of robots competing within a two-dimensional battlefield. This RRobots simulation has been enhanced to support adaptive-systems research efforts probability based behavior selection and self-healing systems. It supports experiment automation. Researchers have used this as a framework to explore the speed of adaptation. New reporting data elements were added to the output system. The team added tools to support the execution of large numbers of simulation runs, distributing these runs within federation of RRobots Ruby on Rails servers. The initial generation of experiment results using a large data set is analyzed. Next-generation job processing components within the RRobots code are also discussed. This paper discusses these improvements from the general RRobots baseline and uses these to compare a faster more reliable RRobots code base with the original simulation.

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Following the Problem Organisation: A Design Strategy for Engineering Emergence

Cited by 2 publications

References 9 publications

A Cooperative Multi-Agent System for Crowd Sensing Based Estimation in Smart Cities

A Cooperative Multi-Agent System for Crowd Sensing Based Estimation in Smart Cities

Researching Adaptive Systems with RRobots

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