Meta-Decision Layer for AI: A Framework for Adaptive Decision-Making in Multi-Agent AI Systems

This research hypothesis proposes a meta-decision layer for AI systems: a control layer that determines not only which action should be taken, but also which decision-making mode should be used before an action is selected.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-30
DOI
https://doi.org/10.5281/zenodo.23070360
Primary Topic
Reinforcement Learning in Robotics
Type
preprint
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preprint

Meta-Decision Layer for AI: A Framework for Adaptive Decision-Making in Multi-Agent AI Systems

AXRIMA
Zenodo (CERN European Organization for Nuclear Research)
Reinforcement Learning in Robotics
preprint

Meta-Decision Layer for AI: A Framework for Adaptive Decision-Making in Multi-Agent AI Systems

AXRIMA
preprint en

Abstract

This research hypothesis proposes a meta-decision layer for AI systems: a control layer that determines not only which action should be taken, but also which decision-making mode should be used before an action is selected.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Reinforcement Learning in Robotics
DOIOpen Access PDFOpenAlex
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Meta-Decision Layer for AI: A Framework for Adaptive Decision-Making in Multi-Agent AI Systems — AXRIMA · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS