Dreaming Is Not a Bug: A Jung-Inspired Dream Layer for Multi-Agent LLM Companions

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteur principal: Cheung, V.
Format: Preprint
Publié: 2026
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866908756719173632
author Cheung, V.
author_facet Cheung, V.
contents Inspired by a personal dream about knowledge-sharing barriers in an everyday hardware project, this paper proposes a Jung-inspired "Dream Layer" for LLM companions, reframing controlled offline hallucinations as a resource for learning and relationship-building rather than a mere reliability bug. Drawing on Jung's notion of the collective unconscious as a shared repository of archetypal forms, we introduce an Artificial Collective Unconscious (ACU): a shared dream pool where agents contribute de-identified, abstract Interaction Templates that are later re-instantiated as idiosyncratic Dream Narratives. The Dream Layer runs strictly offline: logic-enforcing modules are relaxed and sampling temperature is increased, yielding safe but deliberately bizarre narratives (e.g., travel sequences with mismatched currencies) that augment data for rare events and edge-case safety tests; to harness risk productively, we add a governance stack of strict abstraction, temporal delays, and ephemeral memory. Through behavioural simulations of everyday dialogue and long-horizon adaptation tasks, we show that the Dream Layer enables a critical decoupling: agents remain firm on safety constraints (e.g., security policies) while becoming flexible in narrative strategy (e.g., using shared archetypal metaphors to resolve deadlocks), conceptually reframing hallucination so that online, unmarked instances remain bugs, whereas bounded, marked, and delayed ones become a goldmine for synthetic scenarios and deepened companionship, echoing anti-overfitting dream mechanisms proposed in contemporary neuroscience.
format Preprint
id arxiv_https___arxiv_org_abs_2601_06115
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Dreaming Is Not a Bug: A Jung-Inspired Dream Layer for Multi-Agent LLM Companions
Cheung, V.
Artificial Intelligence
Inspired by a personal dream about knowledge-sharing barriers in an everyday hardware project, this paper proposes a Jung-inspired "Dream Layer" for LLM companions, reframing controlled offline hallucinations as a resource for learning and relationship-building rather than a mere reliability bug. Drawing on Jung's notion of the collective unconscious as a shared repository of archetypal forms, we introduce an Artificial Collective Unconscious (ACU): a shared dream pool where agents contribute de-identified, abstract Interaction Templates that are later re-instantiated as idiosyncratic Dream Narratives. The Dream Layer runs strictly offline: logic-enforcing modules are relaxed and sampling temperature is increased, yielding safe but deliberately bizarre narratives (e.g., travel sequences with mismatched currencies) that augment data for rare events and edge-case safety tests; to harness risk productively, we add a governance stack of strict abstraction, temporal delays, and ephemeral memory. Through behavioural simulations of everyday dialogue and long-horizon adaptation tasks, we show that the Dream Layer enables a critical decoupling: agents remain firm on safety constraints (e.g., security policies) while becoming flexible in narrative strategy (e.g., using shared archetypal metaphors to resolve deadlocks), conceptually reframing hallucination so that online, unmarked instances remain bugs, whereas bounded, marked, and delayed ones become a goldmine for synthetic scenarios and deepened companionship, echoing anti-overfitting dream mechanisms proposed in contemporary neuroscience.
title Dreaming Is Not a Bug: A Jung-Inspired Dream Layer for Multi-Agent LLM Companions
topic Artificial Intelligence
url https://arxiv.org/abs/2601.06115