Artificial Immune System Driven Evolution in Swarm Chemistry

Capodieci, Nicola; Hart, Emma; Cabri, Giacomo

doi:10.1109/saso.2014.16

Cited by 4 publications

(2 citation statements)

References 15 publications

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“…Rather than focussing on results, this section highlights the relevant design choices in terms of the framework and discusses the implications of these choices. As each study has been described in detail in previously published conference proceedings, the reader is referred to the corresponding publication 2014b;2014a] for a more detailed discussion of the results.…”

Section: Applicationsmentioning

confidence: 99%

Artificial Immunology for Collective Adaptive Systems Design and Implementation

Capodieci

Hart

Cabri

2016

ACM Trans. Auton. Adapt. Syst.

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Distributed autonomous systems consisting of large numbers of components with no central control point need to be able to dynamically adapt their control mechanisms during run-time in order to deal with an unpredictable and changing environment. Existing frameworks for engineering self-adaptive systems fail to account for the need to incorporate self-expression, i.e. the capability of a system to dynamically adapt its coordination pattern during run-time. Although the benefits of incorporating self-expression are well-known, there is currently no principled means of enabling this during system design. We propose a conceptual framework for principled design of systems that exhibit self-expression, based on inspiration from the natural immune system. The framework is described as a set of design principles and customisable algorithms, and then instantiated in three case-studies, including two from robotics and one from artificial chemistry. We show that it enables self-expression in each case, resulting in systems that are able to adapt their choice of coordination pattern during run time to optimise functional and non-functional goals as well as to discover novel patterns and architectures.

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Section: Applicationsmentioning

confidence: 99%

Artificial Immunology for Collective Adaptive Systems Design and Implementation

Capodieci

Hart

Cabri

2016

ACM Trans. Auton. Adapt. Syst.

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“…The self-organisation of architecture is indeed the topic of ongoing research, and in many places has looked to biological systems for inspiration. Capodieci and Hart [1], for example, demonstrate a wide range of architectures emerging from self-organisation behaviour of nodes, inspired by swarm chemistry.…”

Section: Related Workmentioning

confidence: 99%

Self-Organising Zooms for Decentralised Redundancy Management in Visual Sensor Networks

Esterle

Rinner

Lewis

2015

2015 IEEE 9th International Conference on Self-Adaptive and Self-Organizing Systems

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Abstract-When visual sensor networks are composed of cameras which can adjust the zoom factor of their own lens, one must determine the optimal zoom levels for the cameras, for a given task. This gives rise to an important trade-off between the overlap of the different cameras' fields of view, providing redundancy, and image quality. In an object tracking task, having multiple cameras observe the same area allows for quicker recovery, when a camera fails. In contrast having narrow zooms allow for a higher pixel count on regions of interest, leading to increased tracking confidence. In this paper we propose an approach for the self-organisation of redundancy in a distributed visual sensor network, based on decentralised multi-objective online learning using only local information to approximate the global state. We explore the impact of different zoom levels on these trade-offs, when tasking omnidirectional cameras, having perfect 360-degree view, with keeping track of a varying number of moving objects. We further show how employing decentralised reinforcement learning enables zoom configurations to be achieved dynamically at runtime according to an operator's preference for maximising either the proportion of objects tracked, confidence associated with tracking, or redundancy in expectation of camera failure. We show that explicitly taking account of the level of overlap, even based only on local knowledge, improves resilience when cameras fail. Our results illustrate the trade-off between maintaining high confidence and object coverage, and maintaining redundancy, in anticipation of future failure. Our approach provides a fully tunable decentralised method for the self-organisation of redundancy in a changing environment, according to an operator's preferences.

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