CAMELEON: Cognitively Adaptive Memory with Emotion-weighted Layered Expert Orchestration Network

We present CAMELEON — a conceptual architecture for AI agents that grow more personalised through lived interaction rather than retraining. The architecture combines emotion-weighted context compression, interpretable domain-expert routing via keyword saliency scoring, speculative context pre-activation, and time-decay relevance scoring...

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-17
DOI
https://doi.org/10.5281/zenodo.20726338
Primary Topic
Multimodal Machine Learning Applications
Type
preprint
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preprint

CAMELEON: Cognitively Adaptive Memory with Emotion-weighted Layered Expert Orchestration Network

Rajkumar Arumugam
Zenodo (CERN European Organization for Nuclear Research)
Multimodal Machine Learning Applications
preprint

CAMELEON: Cognitively Adaptive Memory with Emotion-weighted Layered Expert Orchestration Network

Rajkumar Arumugam
preprint en

Abstract

We present CAMELEON — a conceptual architecture for AI agents that grow more personalised through lived interaction rather than retraining. The architecture combines emotion-weighted context compression, interpretable domain-expert routing via keyword saliency scoring, speculative context pre-activation, and time-decay relevance scoring...

Zenodo (CERN European Organization for Nuclear Research)
Multimodal Machine Learning Applications
DOIOpen Access PDFOpenAlex
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CAMELEON: Cognitively Adaptive Memory with Emotion-weighted Layered Expert Orchestration Network — Rajkumar Arumugam · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS