Controlling Large-Scale Self-Organized Networks with Lightweight Cost for Fast Adaptation to Changing Environments

Kuze, Naomi; Kominami, Daichi; Kashima, Kenji; Hashimoto, Takuya; Murata, Masayuki

doi:10.1145/2856424

Cited by 8 publications

(3 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Interestingly, the fact that rules 60 and 90 have been found to have the highest synergy is consistent with the crucial role played by xor gates in cryptography. 8…”

Section: Pure Synergy: Rules 60 and 90mentioning

confidence: 99%

“…Additionally, self-organisation serves as inspiration for new paradigms of de-centralised organisation where order is established spontaneously without relying on an all-knowning architect or a predefined plan, such as with the Internet of Things [ 4 , 5 ] and blockchain technologies [ 6 ]. In this context, self-organisation is regarded as an attractive principle for enabling robustness, adaptability and scalability into the design and managment of large-scale complex networks [ 7 , 8 , 9 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Information-Theoretic Approach to Self-Organisation: Emergence of Complex Interdependencies in Coupled Dynamical Systems

Rosas

Mediano

Ugarte

2018

Entropy

View full text Add to dashboard Cite

Self-organisation lies at the core of fundamental but still unresolved scientific questions, and holds the promise of de-centralised paradigms crucial for future technological developments. While self-organising processes have been traditionally explained by the tendency of dynamical systems to evolve towards specific configurations, or attractors, we see self-organisation as a consequence of the interdependencies that those attractors induce. Building on this intuition, in this work we develop a theoretical framework for understanding and quantifying self-organisation based on coupled dynamical systems and multivariate information theory. We propose a metric of global structural strength that identifies when self-organisation appears, and a multi-layered decomposition that explains the emergent structure in terms of redundant and synergistic interdependencies. We illustrate our framework on elementary cellular automata, showing how it can detect and characterise the emergence of complex structures. I see it" logic, which might eventually prevent further systematic developments [24]. Formulating formal definitions of self-organisation is challenging, partly because self-organisation has been used in diverse contexts and with different purposes [25], and partly due to the fact that the basic notions of "self" and "organisation" are already problematic themselves [26].The absence of an agreed formal definition, combined with the relevance of this notion for scientific and technological advances, generates a need for further explorations about the principles of self-organisation. Scope of this Work and ContributionIn the spirit of Reference [27], we explore to what extent an information-theoretic perspective can illuminate the inner workings of self-organising processes. Due to the connections between information theory and thermodynamics [28,29], our approach can be seen as an extension of previous works that relate self-organisation and statistical physics (see e.g. [30][31][32]). In previous research, self-organisation has been associated with a reduction in the system's entropy [30,33,34] -in contrast, we argue that entropy reduction alone is not a robust predictor of self-organisation, and additional metrics are required.This work establishes a way of understanding self-organising processes that is consistent with the Bayesian interpretation of information theory, as described in Reference [28]. One contribution of our approach is to characterise self-organising processes using multivariate information-theoretic toolsor, put differently, to provide a more fine-grained description of the underlying phenomena behind entropy reduction. We propose that self-organising processes are driven by spontaneous creation of interdependencies, while the reduction of entropy is a mere side effect of this. Following this rationale, we propose the binding information [35] as a metric of the strength of the interdependencies in out-of-equilibrium dynamical systems.Another contribution of our framework is to propose a multi-layer...

show abstract

“…Interestingly, the fact that rules 60 and 90 have been found to have the highest synergy is consistent with the crucial role played by xor gates in cryptography. 8…”

Section: Pure Synergy: Rules 60 and 90mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Information-Theoretic Approach to Self-Organisation: Emergence of Complex Interdependencies in Coupled Dynamical Systems

Rosas

Mediano

Ugarte

2018

Entropy

View full text Add to dashboard Cite

show abstract

“…Self-organization has been widely studied as an attractive approach for realizing adaptability, robustness, and scalability of large-scale complex systems [ 8 ]. For instance, controlling large-scale self-organized networks is presented in [ 9 , 10 ], and Ref. [ 11 ] presents a novel distributed algorithm for multiple unmanned aerial vehicles (UAVs) for a search-attack mission self-organization problem.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Information Sharing with Ontological Relevance Computation for Decentralized Self-Organization Systems

Liu

Ran

Nantogma

et al. 2021

Entropy

View full text Add to dashboard Cite

Decentralization is a peculiar characteristic of self-organizing systems such as swarm intelligence systems, which function as complex collective responsive systems without central control and operates based on contextual local coordination among relatively simple individual systems. The decentralized particularity of self-organizing systems lies in their capacity to spontaneously respond to accommodate environmental changes in a cooperative manner without external control. However, if members cannot obtain observations of the state of the whole team and environment, they have to share their knowledge and policies with each other through communication in order to adapt to the environment appropriately. In this paper, we propose an information sharing mechanism as an independent decision phase to improve individual members’ joint adaption to the world to fulfill an optimal self-organization in general. We design the information sharing decision analogous to human information sharing mechanisms. In this case, information can be shared among individual members by evaluating the semantic relationship of information based on ontology graph and their local knowledge. That is, if individual member collects more relevant information, the information will be used to update its local knowledge and improve sharing relevant information by measuring the ontological relevance. This will enable more related information to be acquired so that their models will be reinforced for more precise information sharing. Our simulations and experimental results show that this design can share information efficiently to achieve optimal adaptive self-organizing systems.

show abstract

Node Assignment-Based Routing for Low-Earth Orbit Satellite Navigation Augmentation Networks

Hou¹,

Fan²,

Yi³

et al. 2022

Lecture Notes in Electrical Engineering

View full text Add to dashboard Cite

Controlling Large-Scale Self-Organized Networks with Lightweight Cost for Fast Adaptation to Changing Environments

Cited by 8 publications

References 26 publications

An Information-Theoretic Approach to Self-Organisation: Emergence of Complex Interdependencies in Coupled Dynamical Systems

An Information-Theoretic Approach to Self-Organisation: Emergence of Complex Interdependencies in Coupled Dynamical Systems

Adaptive Information Sharing with Ontological Relevance Computation for Decentralized Self-Organization Systems

Node Assignment-Based Routing for Low-Earth Orbit Satellite Navigation Augmentation Networks

Contact Info

Product

Resources

About