Cognition all the way down 2.0: neuroscience beyond neurons in the diverse intelligence era

Abstract This paper formalizes biological intelligence as search efficiency in multi-scale problem spaces, aiming to resolve epistemic deadlocks in the basal “cognition wars” unfolding in the Diverse Intelligence research program. It extends classical work on symbolic problem-solving to define a novel problem space lexicon and search efficiency metric . Construed as an operationalization of intelligence, this metric is the decimal logarithm of the ratio between the cost of a random walk and that of a biological agent. Thus, the search efficiency measures how many orders of magnitude of dissipative work an agentic policy saves relative to a maximal-entropy search strategy. Empirical models for amoeboid chemotaxis and barium-induced planarian head regeneration show that, under conservative (i.e., intelligence- underestimating ) assumptions, even ‘simple’ organisms are from two-hundred- to sextillion-fold more efficient in problem space exploration. In this sense, the deep insights of neuroscience are not about neurons per se , but about the policies and patterns of physics and mathematics that function as a kind of “cognitive glue” binding parts toward higher levels of collective intelligence in wholes of highly diverse composition and origin. Therefore, our synthesis argues that the “mark of the cognitive” is perhaps better sought in the measurable efficiency with which living systems, from single cells to complex organisms, traverse energy and information gradients to tame combinatorial explosions-one problem space at a time.

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Publication Details

Journal
Synthese
Published
2025-11-06
DOI
https://doi.org/10.1007/s11229-025-05319-6
Citations
4
Primary Topic
Slime Mold and Myxomycetes Research
Type
article
Field-Weighted Citation Impact
2.70

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article

Cognition all the way down 2.0: neuroscience beyond neurons in the diverse intelligence era

Robert Chis-Ciure, Michael Levin
4 citations
Synthese
Slime Mold and Myxomycetes Research
2.70
article

Cognition all the way down 2.0: neuroscience beyond neurons in the diverse intelligence era

Robert Chis-Ciure, Michael Levin
article en
4 citations

Abstract

Abstract This paper formalizes biological intelligence as search efficiency in multi-scale problem spaces, aiming to resolve epistemic deadlocks in the basal “cognition wars” unfolding in the Diverse Intelligence research program. It extends classical work on symbolic problem-solving to define a novel problem space lexicon and search efficiency metric . Construed as an operationalization of intelligence, this metric is the decimal logarithm of the ratio between the cost of a random walk and that of a biological agent. Thus, the search efficiency measures how many orders of magnitude of dissipative work an agentic policy saves relative to a maximal-entropy search strategy. Empirical models for amoeboid chemotaxis and barium-induced planarian head regeneration show that, under conservative (i.e., intelligence- underestimating ) assumptions, even ‘simple’ organisms are from two-hundred- to sextillion-fold more efficient in problem space exploration. In this sense, the deep insights of neuroscience are not about neurons per se , but about the policies and patterns of physics and mathematics that function as a kind of “cognitive glue” binding parts toward higher levels of collective intelligence in wholes of highly diverse composition and origin. Therefore, our synthesis argues that the “mark of the cognitive” is perhaps better sought in the measurable efficiency with which living systems, from single cells to complex organisms, traverse energy and information gradients to tame combinatorial explosions-one problem space at a time.

SyntheseVol. 206(5)
Tufts University (US), University of Sussex (GB), Institute of Neurobiology (BG)
John Templeton Foundation
Openalex Percentile: Top 9%
Slime Mold and Myxomycetes Research
2.70
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Cognition all the way down 2.0: neuroscience beyond neurons in the diverse intelligence era — Robert Chis-Ciure, Michael Levin · Synthese (2025) | TGRS Research Map | TGRS