Case Study of Novelty, Complexity, and Adaptation in a Multicellular System

Matthew Andres Moreno, Santiago Rodriguez Papa, & Charles Ofria

BEACON Congress

August 19, 2021

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Fraternal Transitions in Individuality

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• fraternal: kin unite to form a new self-replicating entity
• e.g., multicellularity, eusociality

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Wing-Chi Poon / CC BY-SA (https://creativecommons.org/licenses/by-sa/2.5)

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DISHTINY Model

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functional consequences:

• resource distribution
• group expiration
• sufficient for characteristic multicellular traits
• (Moreno, 2019; Moreno, 2021a)

Case Study Data

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Randomly

Generated

Ancestors

14.4k tiles

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“stint”

3 hr x

4 🧵

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Ancestors

14.4k tiles

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3 hr x

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…100x

~20k cell generations

14.4k tiles

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“stint”

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“series”

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3 hr x

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“stint”3 hr x

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…100x

“series”

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“stint”3 hr x

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…100x

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…100x

“series”

…40x

Results

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Part I: Qualitative Morphological Novelty

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morph

phenotype

morph

phenotype

stint

0

1

2

14

15

39

45

stint

59

74

100

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stint 0

morph a

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stint 14

morph d

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stint 15

morph e

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stint 45

morph g

Part II: Adaptation

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Stintwise Fitness Differential

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Stintwise Fitness Differential

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Stintwise Fitness Differential

Part III: “Sequence Complexity”

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Sequence Complexity (Adami, 2000) (Dolson, 2019)

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Sequence Complexity

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Sequence Complexity

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Sequence Complexity

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Sequence Complexity

Part IV: “Interface Complexity”

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Interface

Complexity

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inputs

outputs

messages

Interface

Complexity

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how many

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Conclusion

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Anecdotal Takeaways

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• novelty, complexity, & adaptation appear loosely coupled
• although novelty was sometimes adaptive, these innovations did not yield exceptional fitness increases
• at times, opposite signals from “sequence complexity” and “interface complexity”

Future Work

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• flesh out our adaptation assay
• noncritical sequence complexity

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• sexual recombination & crossover
• ecology

Acknowledgement

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• We are the Digital Evolution Laboratory at the Michigan State University Department of Computer Science and Engineering, in association with the NSF BEACON Center for the Study of Evolution in Action.
• This research was supported in part by NSF grants DEB-1655715 and DBI-0939454. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1424871.

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Matthew

Santiago

Charles

Katherine Perry

References

@MorenoMatthewA

Ackley, David H., and Daniel C. Cannon. "Pursue robust indefinite scalability." HotOS. 2011.

Adami, Christoph, Charles Ofria, and Travis C. Collier. "Evolution of biological complexity." Proceedings of the National Academy of Sciences 97.9 (2000): 4463-4468.

Banzhaf, Wolfgang, et al. "Defining and simulating open-ended novelty: requirements, guidelines, and challenges." Theory in Biosciences 135.3 (2016): 131-161.

Dolson, Emily L., et al. "The MODES toolbox: Measurements of open-ended dynamics in evolving systems." Artificial life 25.1 (2019): 50-73.

Goldsby, Heather J., et al. "The evolutionary origin of somatic cells under the dirty work hypothesis." PLoS biology 12.5 (2014): e1001858.

Heinemann, Christian. "Artificial Life Environment." Informatik-Spektrum 31.1 (2008): 55-61.

Maynard Smith, John; Szathmáry, Eörs (1995). The Major Transitions in Evolution. Oxford, England: Oxford University Press. ISBN 978-0-19-850294-4.

Moreno, Matthew Andres, and Charles Ofria. "Toward open-ended fraternal transitions in individuality." Artificial life 25.2 (2019): 117-133.

Moreno, Matthew Andres, and Charles Ofria. "Exploring Evolved Multicellular Life Histories in a Open-Ended Digital Evolution System." arXiv preprint arXiv:2104.10081 (2021a).

Moreno, Matthew Andres, Santiago Rodriguez Papa, and Charles Ofria. "Conduit: A C++ Library for Best-effort High Performance Computing." arXiv preprint arXiv:2105.10486 (2021b).

Rocki, K., Van Essendelft, D., Sharapov, I., Schreiber, R., Morrison, M., Kibardin, V., ... & James, M. (2020, November). Fast stencil-code computation on a wafer-scale processor. In SC20: International Conference for High Performance Computing, Networking, Storage and Analysis (pp. 1-14). IEEE.

Taylor, Tim, et al. "Open-ended evolution: Perspectives from the OEE workshop in York." Artificial life 22.3 (2016): 408-423.

data:

osf.io/prq49/

library:

github.com/mmore500/dishtiny

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supplement:

osf.io/gekc8/

web viewer:

mmore500.com/dishtiny

@MorenoMatthewA

🌟

questions?

Computational Scalability

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• Distributed Best-effort Communication Model
• Indefinite scalability (Ackley, 2011)
• 80% efficiency scaling to 64 nodes (Moreno et al., 2021b)
• Systolic hardware (Rocki, 2020)
• Cerebras CS-2, 850,000 cores

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Major Evolutionary Transitions in Individuality

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• emergence of new self-replicating entities
• formative in natural history, associated with biological complexity and diversity (Smith and Szmarthy, 1995)

Interface

Complexity

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Naive Approach

Messages

Inputs/Outputs

Interface

Complexity

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Interface

Complexity

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Filtering Out Contingency

Messages

Filtering Out Contingency

Messages

Filtering Out Contingency

Messages

Inputs/Outputs

Filtering Out Contingency

Messages

Inputs/Outputs

Filtering Out Contingency

Messages

Inputs/Outputs

Filtering Out Contingency

Messages

Inputs/Outputs

Measuring Sequence Complexity

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Measuring Fitness: Competitions

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Digital Evolution

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• Deme-based model (Goldsby, 2014)

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• Unified spatial realm
• Implicit group replication (Moreno, 2021)
• Parent-child interactions (Moreno, 2021)

multicell

multicells can’t interact