A Study on Autonomous Functional Differentiation of a Group of Agents Inspired by a Cell Differentiation Mechanism of Early Mammalian Embryos

The paper describes a function determination method of an agent in a multi-agent system based on a newly proposed cell differentiation model. Challenges in previous studies in multi-agent systems include dealing with agent failures and being highly dependent on wireless communication. Therefore, we tried to solve these challenges by using cell differentiation in early mammalian embryos, because cells in early mammalian embryos recognize their position and differentiate according to their position in highly robust ways. Namely, we aim to apply the mechanism to the autonomous functional determination of a group of agents that should decide their function according to their relative location in the group. For this aim, the paper proposed an Nf2-Amot complex model of the living cell. The Nf2-Amot model was expected to gain more robust differentiation of living cells. The model together with the conventional model proposed by Caluwé applied to the agents expected to distinguish whether they were located inside or outside of the crowd without any wireless communications. The result showed that the proposed method is more robust than that of using the conventional model.

Authors

Institutions

Publication Details

Journal
Transactions of the Society of Instrument and Control Engineers
Published
2025-01-01
DOI
https://doi.org/10.9746/sicetr.61.330
Primary Topic
Gene Regulatory Network Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Study on Autonomous Functional Differentiation of a Group of Agents Inspired by a Cell Differentiation Mechanism of Early Mammalian Embryos

Yusuke Sakai, Jun Hakura
Transactions of the Society of Instrument and Control Engineers
Gene Regulatory Network Analysis
article

A Study on Autonomous Functional Differentiation of a Group of Agents Inspired by a Cell Differentiation Mechanism of Early Mammalian Embryos

Yusuke Sakai, Jun Hakura
article en

Abstract

The paper describes a function determination method of an agent in a multi-agent system based on a newly proposed cell differentiation model. Challenges in previous studies in multi-agent systems include dealing with agent failures and being highly dependent on wireless communication. Therefore, we tried to solve these challenges by using cell differentiation in early mammalian embryos, because cells in early mammalian embryos recognize their position and differentiate according to their position in highly robust ways. Namely, we aim to apply the mechanism to the autonomous functional determination of a group of agents that should decide their function according to their relative location in the group. For this aim, the paper proposed an Nf2-Amot complex model of the living cell. The Nf2-Amot model was expected to gain more robust differentiation of living cells. The model together with the conventional model proposed by Caluwé applied to the agents expected to distinguish whether they were located inside or outside of the crowd without any wireless communications. The result showed that the proposed method is more robust than that of using the conventional model.

Transactions of the Society of Instrument and Control EngineersVol. 61(6)
Iwate Prefectural University (JP)
Openalex Percentile: Top 87%
Gene Regulatory Network Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.