Biological agents increase causal emergence after learning new memories.

Prior empirical observation from biological systems; motivates investigation in artificial agents.

Source paper

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The Causally Emergent Alignment Hypothesis: Causal Emergence Aligns with and Predicts Final Reward in Reinforcement Learning Agents

(2026) · Federico Pigozzi · Michael Levin

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Communities (3)

community

Causal emergence in biological systems
members_of
Examines how macro-scale causal power exceeds micro-scale in living and learning systems.
Causal emergence in learning agents
members_of
Uses effective information (EI) and coarse-graining to link causal emergence with RL and biological learning.
Causal emergence in learning and adaptation
members_of
Framework measuring how coarse-grained causal structure increases during learning across biological and artificial agents, using effective information and interventional methods.

Questions (1)

question

How causally emergent are artificial agents compared to biological ones?
gates
Core motivating question addressed by the empirical RL study; identified as major knowledge gap.

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

Biological and artificial agents share causal emergence as an axis of learning and reorganization.claim0.892
Interpretive assertion bridging Levin's biological cognition work with artificial RL; extends 'minds at all scales' thesis.
Causal emergence alignment with learning is a shared axis comparing biological and artificial creatures.claim0.846
Assertion that the correlation between causal emergence and learning constitutes another way biological and artificial intelligences converge.
successful agents exhibited causal emergence that was consistently predictive of final reward early in training and whose representational dynamics aligned with reward improvement in most tasks.quote0.838
Load-bearing summary of the main empirical finding that anchors the Causally Emergent Alignment Hypothesis.
Causal emergence can enable causal interventions to create better RL agents.claim0.830
Assertion that understanding causal emergence may lead to methods for manipulating agent representations to improve performance.
Causal emergence may be a previously undisclosed axis of reorganization of neural representations in RL agents.claim0.827
Authors' interpretive assertion that the observed alignment reveals a novel organizing principle of neural representation dynamics.
"The cognitive glue that enables emergent agents to support associative memories over their subunits is neural bioelectricity"quote0.816
Captures the proposed role of bioelectricity in binding cells into unified agents.
Causal emergence provides new perspectives for causal representation learning, interpreting latent variables as emergent causalities.claim0.808
Cross-fertilization claim made in discussion.
Causal emergence measured by NIS+ increases with observational noise but decreases with dynamical noise.finding0.805
Insight that coarse-graining filters external noise but not intrinsic noise.

Cross-corpus bridges (1)

same_concept_as · Nomic cosine

External markdown files that talk about the same concept as this entity.

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Can memories function as active agents that help reify and maintain the self through circular causality?questions/can-memories-function-as-active-agents-that-help.md0.782