English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Systems composed of many interdependent active entities working on shared resources can be challenging to regulate and multi-agent simulation is an efecient means for ending the suitable entities' behaviors. On the other hand, the search space for a stable solution of the system is usually forbidding and hinders any effort to solve the problem using a top-down approach. Furthermore, the complexity of possible global functions to optimize increases rapidly with the size of the system and can prove difecult to deene and/or evaluate at each system simulation step. The difeculty when designing bottom-up systems is to be able to identify all their emergent properties and the parameters to modulate them. Here we propose a local cooperative decision making process that helps to stabilize such systems. These local processes prove to be very efecient to quickly end dynamic equilibrium solutions where the system continues to function and fulells its global function. Regulation emerges from simple local interactions.

Speeding up the Search of a Global Dynamic Equilibrium from a Local Cooperative Decision