Maximizing local information transfer in Boolean networks

Haruna, Taichi; Nakajima, Kohei

doi:10.1088/1367-2630/aadbc3

Cited by 4 publications

(3 citation statements)

References 34 publications

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“…However we phrase it, the idea is that information processing, responsiveness, and problem-solving capacity are optimal when a system is on the edge of instability, near a critical state [149][150][151]. Moreover, long-range correlations (e.g., cooperation between distant, non-neighboring parts) increase near criticality [145].…”

Section: Self-organized Criticalitymentioning

confidence: 99%

Science-Driven Societal Transformation, Part I: Worldview

Boik

2020

Sustainability

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Humanity faces serious social and environmental problems, including climate change and biodiversity loss. Increasingly, scientists, global policy experts, and the general public conclude that incremental approaches to reduce risk are insufficient and transformative change is needed across all sectors of society. However, the meaning of transformation is still unsettled in the literature, as is the proper role of science in fostering it. This paper is the first in a three-part series that adds to the discussion by proposing a novel science-driven research-and-development program aimed at societal transformation. More than a proposal, it offers a perspective and conceptual framework from which societal transformation might be approached. As part of this, it advances a formal mechanics with which to model and understand self-organizing societies of individuals. While acknowledging the necessity of reform to existing societal systems (e.g., governance, economic, and financial systems), the focus of the series is on transformation understood as systems change or systems migration—the de novo development of and migration to new societal systems. The series provides definitions, aims, reasoning, worldview, and a theory of change, and discusses fitness metrics and design principles for new systems. This first paper proposes a worldview, built using ideas from evolutionary biology, complex systems science, cognitive sciences, and information theory, which is intended to serve as the foundation for the R&D program. Subsequent papers in the series build on the worldview to address fitness metrics, system design, and other topics.

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Section: Self-organized Criticalitymentioning

confidence: 99%

Science-Driven Societal Transformation, Part I: Worldview

Boik

2020

Sustainability

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“…One of these dual dynamics is the dynamics of states forming cellular automata, and the other is the dynamics of the LTE. We previously proposed a similar model system based on a Boolean network that maximizes the local mutual information between interacting agents, and we showed that its time evolution rule always degenerates into a critical and highly canalized rule [25]. The major differences between our current model and the previous one are the introduction of space (interacting with the neighborhood) and the use of LTE.…”

Section: Cellular Information Transfer (Cit) System: Formalizations Amentioning

confidence: 97%

Spatiotemporal dynamics driven by the maximization of local information transfer

Nakajima

Haruna

2019

New J. Phys.

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In this paper, a generic type of a spatially extended system, which is driven by the maximization of information transfer in each spatiotemporal point, is proposed. As an expression of the information transfer, transfer entropy is addressed, and a one-dimensional cellular system (whose state transition is governed to maximize the local transfer entropy (LTE) from interacting cells) is introduced. We first show that this system's mechanism of state transition can be considered equivalent to a certain class of cellular automata rules with memory. The spatiotemporal dynamics of the system is then investigated to generate a wide variety of patterns, including spatiotemporal intermittency, according to the length of memory. Furthermore, the spatiotemporal patterns of states and the resulting information dynamics are statistically characterized in detail, expressing the system's diverse nature. In particular, it is found that, within a certain condition of limited memory, even if each cell is driven to maximize the LTE, the entire system cannot reach toward its theoretical maximum value at all due to its intrinsic property, in which the system is dynamically bounding its limit on its own.

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“…However we phrase it, the idea is that information processing, responsiveness, and problem-solving capacity are optimal when a system is on the edge of instability, near a critical state [151][152][153]. Moreover, long-range correlations (e.g., cooperation between distant, non-neighboring parts) increase near criticality [147].…”

Section: Self-organized Criticalitymentioning

confidence: 99%

Science-Driven Societal Transformation, Part I: Worldview

Boik¹

2020

Preprint

View full text Add to dashboard Cite

Humanity faces serious social and environmental problems, including climate change and biodiversity loss. Risks are increasing and conditions deteriorating. Increasingly, scientists, global policy experts, and the general public conclude that incremental approaches are insufficient and transformative change is needed across all sectors of society. However, the meaning of transformation is still unsettled in the literature, as is the proper role of science in fostering it. This paper is the first in a three-part series that adds to the discussion by proposing a novel science-driven research-and-development program aimed at societal transformation. More than a proposal, it offers a perspective and conceptual framework from which societal transformation might be approached and understood. While acknowledging the necessity of reform to existing societal systems (e.g., governance, economic, and financial systems), the focus of the series is on transformation understood as systems change or systems migration—the de novo development of and migration to new societal systems. The series provides definitions, aims, reasoning, worldview, and a theory of change, and discusses fitness metrics and design principles for new systems. This first paper proposes a worldview built using ideas from evolutionary biology, complex systems science, cognitive sciences, and information theory that is intended to serve as the foundation for the R&amp;D program.

show abstract

Maximizing local information transfer in Boolean networks

Cited by 4 publications

References 34 publications

Science-Driven Societal Transformation, Part I: Worldview

Science-Driven Societal Transformation, Part I: Worldview

Spatiotemporal dynamics driven by the maximization of local information transfer

Science-Driven Societal Transformation, Part I: Worldview

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