scholarly journals An Observation-Driven Agent-Based Modeling and Analysis Framework for C. elegans Embryogenesis

PLoS ONE ◽  
2016 ◽  
Vol 11 (11) ◽  
pp. e0166551 ◽  
Author(s):  
Zi Wang ◽  
Benjamin J. Ramsey ◽  
Dali Wang ◽  
Kwai Wong ◽  
Husheng Li ◽  
...  
Keyword(s):  
Agent Based Modeling ◽  
Analysis Framework ◽  
Modeling And Analysis ◽  
Agent Based ◽  
C Elegans

scholarly journals Agent-Based Modeling Framework for Electric Vehicle Adoption Transition in Indonesia

2021 ◽  
Vol 12 (2) ◽  
pp. 73
Author(s):  
Dita Novizayanti ◽  
Eko Agus Prasetio ◽  
Manahan Siallagan ◽  
Sigit Puji Santosa
Keyword(s):  
Electric Vehicles ◽  
Data Analytics ◽  
Agent Based Modeling ◽  
Analysis Framework ◽  
Modeling Framework ◽  
Agent Based ◽  
Twitter Data ◽  
Decision Making Processes ◽  
Electric Vehicle Adoption ◽  
Technical Features

Currently, the adoption of electric vehicles (EV) draws much attention, as the environmental issue of reducing carbon emission is increasing worldwide. However, different countries face different challenges during this transition, particularly developing countries. This research aims to create a framework for the transition to EV in Indonesia through Agent-Based Modeling (ABM). The framework is used as the conceptual design for ABM to investigate the effect of agents’ decision-making processes at the microlevel into the number of adopted EV at the macrolevel. The cluster analysis is equipped to determine the agents’ characteristics based on the categories of the innovation adopters. There are 11 significant variables and four respondents’ clusters: innovators, early majority, late majority, and the uncategorized one. Moreover, Twitter data analytics are utilized to investigate the information engagement coefficient based on the agents’ location. The agents’ characteristics which emerged from this analysis framework will be used as the fundamental for investigating the effect of agents’ specific characteristics and their interaction through ABM for further research. It is expected that this framework will enable the discovery of which incentive scheme or critical technical features effectively increase the uptake of EV according to the agents’ specific characteristics.

scholarly journals Shared behavioral mechanisms underlie C. elegans aggregation and swarming

2018 ◽  
Author(s):  
S Serena Ding ◽  
Linus J. Schumacher ◽  
Avelino E. Javer ◽  
Robert G. Endres ◽  
André EX Brown
Keyword(s):  
A Priori ◽  
Population Level ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Individual Level ◽  
C Elegans ◽  
Behavioral Rules ◽  
Level Statistics ◽  
Approximate Bayesian ◽  
Behavioral Mechanisms

AbstractIn complex biological systems, simple individual-level behavioral rules can give rise to emergent group-level behavior. While such collective behavior has been well studied in cells and larger organisms, the mesoscopic scale is less understood, as it is unclear which sensory inputs and physical processes matter a priori. Here, we investigate collective feeding in the roundworm C. elegans at this intermediate scale, using quantitative phenotyping and agent-based modeling to identify behavioral rules underlying both aggregation and swarming—a dynamic phenotype only observed at longer timescales. Using fluorescent multi-worm tracking, we quantify aggregation behavior in terms of individual dynamics and population-level statistics. Based on our quantification, we use agent-based simulations and approximate Bayesian inference to identify three key behavioral rules that give rise to aggregation: cluster-edge reversals, a density-dependent switch between crawling speeds, and taxis towards neighboring worms. Our simulations suggest that swarming is simply driven by local food depletion but otherwise employs the same behavioral mechanisms as the initial aggregation. Hence, mesoscopic C. elegans uses mechanisms familiar from microscopic systems for aggregation, but implemented via more complex behaviors characteristic of macroscopic organisms.

scholarly journals Applicability of an agent-based modeling concept to modeling of transportation phenomena

2002 ◽  
Vol 12 (2) ◽  
pp. 141-156 ◽  
Author(s):  
Shinya Kikuchi ◽  
Jongho Rhee ◽  
Dusan Teodorovic
Keyword(s):  
Traditional Approach ◽  
Financial Economic ◽  
Transportation Systems ◽  
Behavioral Pattern ◽  
Agent Based Modeling ◽  
Modeling And Analysis ◽  
Agent Based ◽  
Transportation Problems ◽  
Analysis Process ◽  
The Individual

Today's transportation problems are found in the complex interactions of social, financial, economic, political, and engineering issues. The traditional approach to analyzing transportation problems has been the top-down approach, in which a set of overall objectives is defined and specific parts are fitted in the overall scheme. The effectiveness of this analysis process has been challenged when many issues need to be addressed at once and the individual parts participants to decisions have greater autonomy. A factor contributing to this phenomenon is the greater opportunity and power for individual parts to communicate and to interact with one another. As a result, it has become increasingly difficult to predict or control the overall performance of a large system, or to diagnose particular phenomena. In the past decade, the concept of agent-based modeling has been developed and applied to problems that exhibit a complex behavioral pattern. This modeling approach considers that each part acts on the basis of its local knowledge and cooperates and/or competes with other parts. Through the aggregation of the individual interactions, the overall image of the system emerges. This approach is called the bottom-up approach. This paper examines the link between today's transportation problems and agent-based modeling, presents the framework of agent based modeling, notes recently used examples applied to transportation, and discusses limitations. The intent of this paper is to explore a new avenue for the direction of modeling and analysis of increasingly complex transportation systems.

scholarly journals Shared behavioral mechanisms underlie C. elegans aggregation and swarming

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Siyu Serena Ding ◽  
Linus J Schumacher ◽  
Avelino E Javer ◽  
Robert G Endres ◽  
André EX Brown
Keyword(s):  
A Priori ◽  
Population Level ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Individual Level ◽  
C Elegans ◽  
Behavioral Rules ◽  
Level Statistics ◽  
Approximate Bayesian ◽  
Behavioral Mechanisms

In complex biological systems, simple individual-level behavioral rules can give rise to emergent group-level behavior. While collective behavior has been well studied in cells and larger organisms, the mesoscopic scale is less understood, as it is unclear which sensory inputs and physical processes matter a priori. Here, we investigate collective feeding in the roundworm C. elegans at this intermediate scale, using quantitative phenotyping and agent-based modeling to identify behavioral rules underlying both aggregation and swarming—a dynamic phenotype only observed at longer timescales. Using fluorescence multi-worm tracking, we quantify aggregation in terms of individual dynamics and population-level statistics. Then we use agent-based simulations and approximate Bayesian inference to identify three key behavioral rules for aggregation: cluster-edge reversals, a density-dependent switch between crawling speeds, and taxis towards neighboring worms. Our simulations suggest that swarming is simply driven by local food depletion but otherwise employs the same behavioral mechanisms as the initial aggregation.

scholarly journals Systemic Agent-Based Modeling and Analysis of Passenger Discretionary Activities in Airport Terminals

Aerospace ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 162
Author(s):  
Adin Mekić ◽  
Seyed Sahand Mohammadi Ziabari ◽  
Alexei Sharpanskykh
Keyword(s):  
Agent Based Modeling ◽  
Aviation Industry ◽  
Operational Strategies ◽  
Modeling And Analysis ◽  
Agent Based ◽  
Terminal Performance ◽  
Airport Terminal ◽  
Airport Terminals ◽  
Terminal Operations ◽  
Retail Food

Discretionary activities such as retail, food, and beverages generate a significant amount of non-aeronautical revenue within the aviation industry. However, they are rarely taken into account in computational airport terminal models. Since discretionary activities affect passenger flow and global airport terminal performance, discretionary activities need to be studied in detail. Additionally, discretionary activities are influenced by other airport terminal processes, such as check-in and security. Thus, discretionary activities need to be studied in relation to other airport terminal processes. The aim of this study is to analyze discretionary activities in a systemic way, taking into account interdependencies with other airport terminal processes and operational strategies used to manage these processes. An agent-based simulation model for airport terminal operations was developed, which covers the main handling processes and passenger decision-making with discretionary activities. The obtained simulation results show that operational strategies that reduce passenger queue time or increase passenger free time can significantly improve global airport terminal performance through efficiency, revenue, and cost.

Sign in / Sign up

Export Citation Format

Share Document