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  Environmental variability and network structure determine the optimal plasticity mechanisms in embodied agents

Giannakakis, E., Khajehabdollahi, S., & Levina, A. (2023). Environmental variability and network structure determine the optimal plasticity mechanisms in embodied agents. In H. Iizuka, K. Suzuki, R. Uno, L. Damiano, N. Spychala, M. Aguilera, et al. (Eds.), ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference (pp. 157-166). MIT Press. doi:10.1162/isal_a_00606.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-ADDB-A Version Permalink: https://hdl.handle.net/21.11116/0000-000E-6C1D-A
Genre: Conference Paper

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Locator:
https://direct.mit.edu/isal/proceedings/isal/35/22/116832 (Publisher version)
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 Creators:
Giannakakis, E1, Author                 
Khajehabdollahi, S, Author                 
Levina, A1, Author           
Affiliations:
1Institutional Guests, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_3505519              

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 Abstract: The evolutionary balance between innate and learned behaviors is highly intricate, and different organisms have found different solutions to this problem. We hypothesize that the emergence and exact form of learning behaviors is naturally connected with the statistics of environmental fluctuations and tasks an organism needs to solve. Here, we study how different aspects of simulated environments shape an evolved synaptic plasticity rule in static and moving artificial agents. We demonstrate that environmental fluctuation and uncertainty control the reliance of artificial organisms on plasticity. Interestingly, the form of the emerging plasticity rule is additionally determined by the details of the task the artificial organisms are aiming to solve. Moreover, we show that co-evolution between static connectivity and interacting plasticity mechanisms in distinct sub-networks changes the function and form of the emerging plasticity rules in embodied agents performing a foraging task.

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 Dates: 2023-072023
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1162/isal_a_00606
 Degree: -

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Title: ALIFE 2023: Ghost in the Machine: The 2021 Conference on Artificial Life
Place of Event: Sapporo, Japan
Start-/End Date: 2023-07-24 - 2023-07-28

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Title: ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference
Source Genre: Proceedings
 Creator(s):
Iizuka, H, Editor
Suzuki, K, Editor
Uno, R, Editor
Damiano, L, Editor
Spychala, N, Editor
Aguilera, M, Editor
Izquierdo, E, Editor
Suzuki, R, Editor
Baltieri, M, Editor
Affiliations:
-
Publ. Info: MIT Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 157 - 166 Identifier: DOI: 10.1162/isal_a_00704