MODEE-LID: Multiobjective Design of Energy-Efficient Hardware Accelerators for Levodopa-Induced Dyskinesia Classifiers

Hurta, Martin; Mrázek, Vojtěch; Drahosova, Michaela; Sekanina, Lukáš

doi:10.1109/ddecs57882.2023.10139399

2023 26th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS) 2023

DOI: 10.1109/ddecs57882.2023.10139399

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MODEE-LID: Multiobjective Design of Energy-Efficient Hardware Accelerators for Levodopa-Induced Dyskinesia Classifiers

Martin Hurta

Vojtěch Mrázek

Michaela Drahosova

et al.

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2024

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Sustaining Evolution for Shallow Embodied Intelligence

Langdon,

Hulme

2024

IOP Conf. Ser.: Mater. Sci. Eng.

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Lenski’s experiments with E. Coli show Biology can sustain continual evolutionary improvement. However long term evolutionary experiments (LTEE) with evolutionary computing find that information theory’s failed disruption propagation (FDP) in deeply nested genetic programming (GP) hierarchies can greatly slow adaptation. We propose that researchers aiming at embodied artificial intelligence should control software robustness by using porous high surface area geometrical architectures, perhaps composed of many shallow mangrove like tree structures intimately linked to their data rich fitness environment.

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Sustaining Evolution for Shallow Embodied Intelligence

Langdon,

Hulme

2024

IOP Conf. Ser.: Mater. Sci. Eng.

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MODEE-LID: Multiobjective Design of Energy-Efficient Hardware Accelerators for Levodopa-Induced Dyskinesia Classifiers

Cited by 1 publication

References 11 publications

Sustaining Evolution for Shallow Embodied Intelligence

Sustaining Evolution for Shallow Embodied Intelligence

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