A Generalisable Measure of Self-Organisation and Emergence

Wright, W.A.; Smith, Robert E.; Daněk, Martin; Greenway, Phil

doi:10.1007/3-540-44668-0_119

Cited by 19 publications

(8 citation statements)

References 8 publications

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“…Predictability is particularly important in relation to phase boundaries where fundamental changes in behaviour occur [28]. As Wright et al note, in real-world systems ".. the presence of undesirable behaviours that are a result of unforeseen non-linear interactions with the different components of these systems ... can have catastrophic consequences ..." [29]. If predictability cannot be guaranteed, at least within acceptable bounds, swarm intelligence systems will not be used for safety critical applications a priori.…”

Section: The 'Curse' Of Emergencementioning

confidence: 99%

The Blessing and Curse of Emergence in Swarm Intelligence Systems

Harvey

2018

Foundations of Trusted Autonomy

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Section: The 'Curse' Of Emergencementioning

confidence: 99%

The Blessing and Curse of Emergence in Swarm Intelligence Systems

Harvey

2018

Foundations of Trusted Autonomy

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“…Those varriations in regularity can be measured in a practical way using an approximation of the eective number of degrees of freedom using a straightforwrd linear annalysis [17], [10]. This number is calculated every 100 steps with the values of neurons' membrane potentials in the last 100 steps.…”

Section: Recurrent Networkmentioning

confidence: 99%

Temporal pattern identification using spike-timing dependent plasticity

Henry

Daucé

Soula³

2007

Neurocomputing

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This paper addresses the question of the functional role of the dual application of positive and negative Hebbian time dependent plasticity rules, in the particular framework of reinforcement learning tasks. Our simulations take place in a recurrent network of spiking neurons with inhomogeneous synaptic weights. The network spontaneously displays a self-sustained activity.A Spike-Timing Dependent Plasticity (STDP) rule is combined with its opposite, the anti-STDP. A local regulation mechanism moreover maintains the output neuron in the vicinity of a reference frequency, which forces the global dynamics to be maintained in a softly disordered regime.This approach is tested on a simple discrimination task which requires short-term memory : temporal pattern identication. We show that such temporal patterns can be categorized, and present tracks for future improvements.

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“…233-235). Ways to measure macroscopic features of complex agent-based systems, such as emergence, were already presented in the literature [2,3]. However, complexity phenomena and emergence, when subjectively observed, thus far have mostly been described qualitatively in publications on multiagent systems.…”

Section: Brief Introduction Problem Statement and Research Goalsmentioning

confidence: 99%

A Toolbox to Analyze Emergence in Multiagent Simulations

Saft¹,

Nissen²

2017

Multi-Agent Systems

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The field of complexity science often employs multiagent simulations to investigate complex and emergent behavior. Authors in complexity science have suggested that the discussion of complex systems could benefit from a more systematic approach and a more compact mathematical way to describe the behavior of such systems in addition to the common observations and interpretations taking place today. Regarding quantitative measures to capture emergent phenomena, several approaches have been published, buthave not yet been put to wide systematic use in the research community. One reason for this could be the manual effort required to investigate multiagent systems in a quantitatively accurate form. Toward this end, there has so far been a lack of appropriate and easy-to-use IT-based tools. To eliminate this deficiency, we present a software library, which enables researchers to integrate emergence measurements into experiments with multiagent modeling tools such as Repast and NetLogo. The major benefit for researchers is that this toolbox enables them to make comparable, quantitatively wellgrounded statements about the emergent behavior of the model at hand. The toolbox therefore provides researchers with a standardized artifact that can be employed in a systematic methodological approach to the analysis of multiagent systems.

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A Generalisable Measure of Self-Organisation and Emergence

Cited by 19 publications

References 8 publications

The Blessing and Curse of Emergence in Swarm Intelligence Systems

The Blessing and Curse of Emergence in Swarm Intelligence Systems

Temporal pattern identification using spike-timing dependent plasticity

A Toolbox to Analyze Emergence in Multiagent Simulations

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