Relational Reversibility: Structural Conditions for Recovery Capacity Generation in Adaptive Multi-Agent Systems

RT4 studies how interaction changes a declared system's ability to recover after disruption. It distinguishes recovery supplied by current support from capacity retained after earlier cooperative learning or repair, and separates autonomous, assisted, and preparation effects. Support paths and failure-transmission paths are treated as different objects. An exact finite-cascade benchmark isolates support loss, transmission removal, and the task cost of hub removal. A trust-connectivity score remains a candidate predictor rather than a general recovery probability. Unreproducible demonstrations and an undocumented collaboration analysis are retired; causal capacity-generation mechanisms and incremental predictive value require direct experiments.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-10
DOI
https://doi.org/10.5281/zenodo.18795504
Primary Topic
Ecosystem dynamics and resilience
Type
article
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article

Relational Reversibility: Structural Conditions for Recovery Capacity Generation in Adaptive Multi-Agent Systems

Bin Seol
Zenodo (CERN European Organization for Nuclear Research)
Ecosystem dynamics and resilience
article

Relational Reversibility: Structural Conditions for Recovery Capacity Generation in Adaptive Multi-Agent Systems

Bin Seol
article en

Abstract

RT4 studies how interaction changes a declared system's ability to recover after disruption. It distinguishes recovery supplied by current support from capacity retained after earlier cooperative learning or repair, and separates autonomous, assisted, and preparation effects. Support paths and failure-transmission paths are treated as different objects. An exact finite-cascade benchmark isolates support loss, transmission removal, and the task cost of hub removal. A trust-connectivity score remains a candidate predictor rather than a general recovery probability. Unreproducible demonstrations and an undocumented collaboration analysis are retired; causal capacity-generation mechanisms and incremental predictive value require direct experiments.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 83%
Ecosystem dynamics and resilience
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