Evidence map›Paper›PMID 37006601›Full record

ArticlePerspectives on behavior science2023

Creating and Studying the Behavior of Artificial Organisms Animated by an Evolutionary Theory of Behavior Dynamics.

J J McDowell

Abstract read
In one paragraph

Article in Perspectives on behavior science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Twiddling Bits.Perspectives on behavior science · 2026
    Article
  2. Article
  3. I'm Not Like the Others: Atypical Research Subjects in JEAB Publications.Journal of the experimental analysis of behavior · 2025
    Review
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

J J McDowellDepartment of Psychology, Emory University, 36 Eagle Row, Atlanta, GA 30322 USA.ORCID 0000-0003-0953-9128

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The evolutionary theory of behavior dynamics (ETBD) is a complexity theory, which means that it is stated in the form of simple low-level rules, the repeated operation of which generates high-level outcomes that can be compared to data. The low-level rules of the theory implement Darwinian processes of selection, reproduction, and mutation. This tutorial is an introduction to the ETBD for a general audience, and illustrates how the theory is used to animate artificial organisms that can behave continuously in any experimental environment. Extensive research has shown that the theory generates behavior in artificial organisms that is indistinguishable in qualitative and quantitative detail from the behavior of live organisms in a wide variety of experimental environments. An overview and summary of this supporting evidence is provided. The theory may be understood to be computationally equivalent to the biological nervous system, which means that the algorithmic operation of the theory and the material operation of the nervous system give the same answers. The applied relevance of the theory is also discussed, including the creation of artificial organisms with various forms of psychopathology that can be used to study clinical problems and their treatment. Finally, possible future directions are discussed, such as the extension of the theory to behavior in a two-dimensional grid world.

Indexed as

adaptive behaviorbehavior dynamicscomplexity theoryevolutionary dynamicsneural Darwinismselection by consequences

Identifiers

PMID37006601
PMCPMC10050662

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.