Toward Controlling a Cyber-Physical System using Synthetic Biological Intelligence

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

Abstract

Artificial Intelligence (AI) tools such as ChatGPT have transformed our daily life. Usually, these AI tools are based on Neural Networks (NNs) implemented in digital hardware, i.e., not biological or physical NNs like those found in human brains. Instead, NNs are typically implemented as software on top of a Graphics Processing Unit (GPU) or specialized AI hardware. In contrast, this work-in-progress utilizes a biological NN, demonstrating the use of Synthetic Biological Intelligence (SBI) by implementing a toy example - controlling an inverted pendulum. Biological NNs can be beneficial compared to GPUs or specialized AI hardware, especially in terms of energy efficiency and capability on noisy or dynamic tasks. Following the encoding, decoding, reward, and punishment nature of the biological NN, this work presents initial results toward controlling the physical system in future research.

Details

Original languageEnglish
Title of host publicationNanoCom 2025 - Proceedings of the 12th ACM International Conference on Nanoscale Computing and Communication
PublisherAssociation for Computing Machinery, Inc
Pages157-158
Number of pages2
ISBN (electronic)9798400721663
Publication statusPublished - 22 Oct 2025
Peer-reviewedYes

Conference

Title12th ACM International Conference on Nanoscale Computing and Communication
Abbreviated titleNanoCom 2025
Conference number12
Duration23 - 25 October 2025
Website
LocationUniversity of Electronic Science and Technology of China
CityChengdu
CountryChina

External IDs

ORCID /0000-0001-8469-9573/work/198590419
ORCID /0000-0001-5410-6810/work/198594991