Multi-level agency

Coarse-graining empowerment

2025-06-09 — 2025-07-09

Wherein the preferred level of abstraction for explaining behaviour is considered, and a concrete mapping between utility and biological fitness across genes, organisms and collectives is examined.

agents
AI safety
bounded compute
collective knowledge
computers are awful together
concurrency hell
distributed
economics
edge computing
extended self
game theory
incentive mechanisms
machine learning
networks

Looking at a complicated system such as a human society or a microchip or a neural network, at what level of abstraction do we want to think about it to best understand what it is doing? E.g. is technology itself an agent?

Probably some classic question about “emergence” and “complexity” and “hierarchy” and “levels of organisation”. We might also think about the modern synthesis of evolutionary biology, which is a theory of how evolution works at different levels of organisation, from genes to organisms to populations.

Figure 1

1 Incoming

2 References

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Costa, Gavenčiak, Hyland, et al. 2025. Possible Principles for Aligned Structure Learning Agents.”
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Hyland, Gavenčiak, Costa, et al. 2024. Free-Energy Equilibria: Toward a Theory of Interactions Between Boundedly-Rational Agents.” In.
Keeney, and Raiffa. 1993. Decisions with Multiple Objectives: Preferences and Value Trade-Offs.
Levin. 2019. The Computational Boundary of a ‘Self’: Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition.” Frontiers in Psychology.
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Okasha, and Okasha. 2008. Evolution and the Levels of Selection.
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