AetherGrid: A Distributed Cognitive-Orchestration Framework Linking Sensory-Emotional Memory Encoding (AetherCore) with Autonomous Agent Governance

This paper introduces AetherGrid, a distributed cognitive-orchestration framework that tightly integrates AetherCore, a sensory-emotional memory encoding subsystem, with an autonomous multi-agent governance fabric. AetherCore encodes multi-modal inputs into affective-semantic embeddings and maintains a temporally-structured emotional memory graph. AetherGrid uses a Model Context Protocol (MCP) and an adaptive orchestration protocol for task decomposition, cross-agent context propagation, and ethical governance. We describe the emotional encoding algorithm, MCP schema, orchestration protocol, and prototype implementation notes. Preliminary simulations show improved context continuity, lower latency for multi-step tasks, and increased affective relevance when AetherCore is integrated. Reproducibility artifacts are provided.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-29
DOI
https://doi.org/10.5281/zenodo.17477225
Primary Topic
Emotion and Mood Recognition
Type
article
Field-Weighted Citation Impact
0.00
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article

AetherGrid: A Distributed Cognitive-Orchestration Framework Linking Sensory-Emotional Memory Encoding (AetherCore) with Autonomous Agent Governance

Zenodo (CERN European Organization for Nuclear Research)
Emotion and Mood Recognition
article

AetherGrid: A Distributed Cognitive-Orchestration Framework Linking Sensory-Emotional Memory Encoding (AetherCore) with Autonomous Agent Governance

article en

Abstract

This paper introduces AetherGrid, a distributed cognitive-orchestration framework that tightly integrates AetherCore, a sensory-emotional memory encoding subsystem, with an autonomous multi-agent governance fabric. AetherCore encodes multi-modal inputs into affective-semantic embeddings and maintains a temporally-structured emotional memory graph. AetherGrid uses a Model Context Protocol (MCP) and an adaptive orchestration protocol for task decomposition, cross-agent context propagation, and ethical governance. We describe the emotional encoding algorithm, MCP schema, orchestration protocol, and prototype implementation notes. Preliminary simulations show improved context continuity, lower latency for multi-step tasks, and increased affective relevance when AetherCore is integrated. Reproducibility artifacts are provided.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 41%
Emotion and Mood Recognition
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