Agent Based Modelling of Smart Structures

2017 ◽  
pp. 38-60
Author(s):  
Andreea Ion ◽  
Monica Patrascu
Keyword(s):  
Large Scale ◽  
Smart Structures ◽  
Simulation Models ◽  
Urban Environments ◽  
Ease Of Use ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Automation Systems ◽  
The Social ◽  
Wide Range

Smart structures are complex systems situated in even more complex and large scale urban environments. This chapter opens the field of agent based modelling and simulation (ABMS) to civil engineers. ABMS offers a wide range of tools for implementing simulation models of systems with high degrees of interconnectivity and a large number of component subsystems. The ease of use for specialized engineers and the capabilities of integration with existent technologies and infrastructures, make agent based models a very attractive way to incorporate the social system in the design process of buildings. Moreover, ABMS allows for the testing and validation of structure wide control and automation systems. This chapter presents past and current efforts of using agent based modelling for smart structures, as well as the main challenges brought by this new interdisciplinary research domain.

scholarly journals An Eco-Friendly Multimodal Route Guidance System for Urban Areas Using Multi-Agent Technology

2021 ◽  
Vol 11 (5) ◽  
pp. 2057
Author(s):  
Abdallah Namoun ◽  
Ali Tufail ◽  
Nikolay Mehandjiev ◽  
Ahmed Alrehaili ◽  
Javad Akhlaghinia ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Urban Areas ◽  
Urban Environments ◽  
Ease Of Use ◽  
Transport Infrastructure ◽  
Guidance System ◽  
Planning System ◽  
Flow Density ◽  
Route Guidance ◽  
Agent Based

The use and coordination of multiple modes of travel efficiently, although beneficial, remains an overarching challenge for urban cities. This paper implements a distributed architecture of an eco-friendly transport guidance system by employing the agent-based paradigm. The paradigm uses software agents to model and represent the complex transport infrastructure of urban environments, including roads, buses, trolleybuses, metros, trams, bicycles, and walking. The system exploits live traffic data (e.g., traffic flow, density, and CO2 emissions) collected from multiple data sources (e.g., road sensors and SCOOT) to provide multimodal route recommendations for travelers through a dedicated application. Moreover, the proposed system empowers the transport management authorities to monitor the traffic flow and conditions of a city in real-time through a dedicated web visualization. We exhibit the advantages of using different types of agents to represent the versatile nature of transport networks and realize the concept of smart transportation. Commuters are supplied with multimodal routes that endeavor to reduce travel times and transport carbon footprint. A technical simulation was executed using various parameters to demonstrate the scalability of our multimodal traffic management architecture. Subsequently, two real user trials were carried out in Nottingham (United Kingdom) and Sofia (Bulgaria) to show the practicality and ease of use of our multimodal travel information system in providing eco-friendly route guidance. Our validation results demonstrate the effectiveness of personalized multimodal route guidance in inducing a positive travel behavior change and the ability of the agent-based route planning system to scale to satisfy the requirements of traffic infrastructure in diverse urban environments.

scholarly journals ABWiSE v1.0: Toward and Agent-Based Approach to Simulating Wildfire Spread

2021 ◽  
Author(s):  
Jeffrey Katan ◽  
Liliana Perez
Keyword(s):  
Human Life ◽  
Simulation Models ◽  
Empirical Models ◽  
Physical Models ◽  
Fire Behaviour ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Fire Front ◽  
Wildfire Simulation ◽  
Behaviour Simulation

Abstract. Wildfires are a complex phenomenon emerging from interactions between air, heat, and vegetation, and while they are an important component of many ecosystems’ dynamics, they pose great danger to those ecosystems, and human life and property. Wildfire simulation models are an important research tool that help further our understanding of fire behaviour and can allow experimentation without recourse to live fires. Current fire simulation models fit into two general categories: empirical models and physical models. We present a new modelling approach that uses agent-based modelling to combine the complexity found in physical models with the ease of computation of empirical models. Our model represents the fire front as a set of moving agents that respond to, and interact with, vegetation, wind, and terrain. We calibrate the model using two simulated fires and one real fire, and validate the model against another real fire and the interim behaviour of the real calibration fire. Our model successfully replicates these fires, with a Figure of Merit on par with simulations by the Prometheus simulation model. Our model is a stepping-stone in using agent-based modelling for fire behaviour simulation, as we demonstrate the ability of agent-based modelling to replicate fire behaviour through emergence alone.

Improving the Efficiency of Large-Scale Agent-Based Models Using Compression Techniques

2012 ◽  
pp. 301-326
Author(s):  
Mitchell Welch ◽  
Paul Kwan ◽  
A.S.M. Sajeev ◽  
Graeme Garner
Keyword(s):  
Large Scale ◽  
Agent Based Models ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Livestock Disease ◽  
Interacting Agents ◽  
National Model ◽  
Complex Phenomena ◽  
Modelling System

Agent-based modelling is becoming a widely used approach for simulating complex phenomena. By making use of emergent behaviour, agent based models can simulate systems right down to the most minute interactions that affect a system’s behaviour. In order to capture the level of detail desired by users, many agent based models now contain hundreds of thousands and even millions of interacting agents. The scale of these models makes them computationally expensive to operate in terms of memory and CPU time, limiting their practicality and use. This chapter details the techniques for applying Dynamic Hierarchical Agent Compression to agent based modelling systems, with the aim of reducing the amount of memory and number of CPU cycles required to manage a set of agents within a model. The scheme outlined extracts the state data stored within a model’s agents and takes advantage of redundancy in this data to reduce the memory required to represent this information. The techniques show how a hierarchical data structure can be used to achieve compression of this data and the techniques for implementing this type of structure within an existing modelling system. The chapter includes a case study that outlines the practical considerations related to the application of this scheme to Australia’s National Model for Emerging Livestock Disease Threats that is currently being developed.

PARALLEL AGENT-BASED SIMULATION ON A CLUSTER OF WORKSTATIONS

2003 ◽  
Vol 13 (04) ◽  
pp. 629-641 ◽  
Author(s):  
Konstantin Popov ◽  
Mahmoud Rafea ◽  
Fredrik Holmgren ◽  
Per Brand ◽  
Vladimir Vlassov ◽  
...  
Keyword(s):  
Web Sites ◽  
Large Scale ◽  
Parallel Implementation ◽  
Simulation Models ◽  
Agent Based Simulation ◽  
Time Step ◽  
Agent Based ◽  
Simulation Step ◽  
Cluster Of Workstations ◽  
Concurrent Simulation

We discuss a parallel implementation of an agent-based simulation. Our approach allows to adapt a sequential simulator for large-scale simulation on a cluster of workstations. We target discrete-time simulation models that capture the behavior of Web users and Web sites. Web users are connected with each other in a graph resembling the social network. Web sites are also connected in a similar graph. Users are stateful entities. At each time step, they exhibit certain behaviour such as visiting bookmarked sites, exchanging information about Web sites in the "word-of-mouth" style, and updating bookmarks. The real-world phenomena of emerged aggregated behavior of the Internet population is studied. The system distributes data among workstations, which allows large-scale simulations infeasible on a stand-alone computer. The model properties cause traffic between workstations proportional to partition sizes. Network latency is hidden by concurrent simulation of multiple users. The system is implemented in Mozart that provides multithreading, dataflow variables, component-based software development, and network-transparency. Currently we can simulate up to 106 Web users on 104 Web sites using a cluster of 16 computers, which takes few seconds per simulation step, and for a problem of the same size, parallel simulation offers speedups between 11 and 14.

scholarly journals SPECIFICATION OF THE SOCIAL FORCE PEDESTRIAN MODEL BY EVOLUTIONARY ADJUSTMENT TO VIDEO TRACKING DATA

2007 ◽  
Vol 10 (supp02) ◽  
pp. 271-288 ◽  
Author(s):  
ANDERS JOHANSSON ◽  
DIRK HELBING ◽  
PRADYUMN K. SHUKLA
Keyword(s):  
Large Scale ◽  
Optimal Parameter ◽  
Video Tracking ◽  
Urban Environments ◽  
Force Model ◽  
Tracking Data ◽  
Social Force ◽  
Social Force Model ◽  
Video Recordings ◽  
The Social

Based on suitable video recordings of interactive pedestrian motion and improved tracking software, we apply an evolutionary optimization algorithm to determine optimal parameter specifications for the social force model. The calibrated model is then used for large-scale pedestrian simulations of evacuation scenarios, pilgrimage, and urban environments.

scholarly journals The Potential of Modeling Process for Social Sciences and Social Work

2021 ◽  
pp. 113-134
Author(s):  
Andrés Lorenzo-Aparicio ◽  
Keyword(s):  
Social Sciences ◽  
Social Workers ◽  
Social Processes ◽  
Social Phenomena ◽  
Agent Based ◽  
Useful Knowledge ◽  
Agent Based Modelling ◽  
Modeling Process ◽  
The Social ◽  
Human Ecosystems

Simplification and necessary reductionism in a model cannot lead to detailed descriptions of social phenomena with all their complexity, but we can obtain useful knowledge from their application both in specific and generic contexts. Human ecosystems, that perform as adaptative complex systems, have features which make it difficult to generate valid models. Amongst them, the emergency phenomena, that presents new characteristics that cannot be explained by the components of the system itself. But without this knowledge derived from modelling, we, as social workers, cannot suggest answers that ignore the structural causes of social problems. Faced with this challenge we propose Agent Based Modelling, as it allows us to study the social processes of human ecosystems and in turn demonstrates new challenges of knowledge and competences that social workers might have.

scholarly journals Feasibility of Repeated Assessment of Cognitive Function in Older Adults Using a Wireless, Mobile, Dry-EEG Headset and Tablet-Based Games

2021 ◽  
Vol 12 ◽  
Author(s):  
Esther C. McWilliams ◽  
Florentine M. Barbey ◽  
John F. Dyer ◽  
Md Nurul Islam ◽  
Bernadette McGuinness ◽  
...  
Keyword(s):  
Large Scale ◽  
Age Groups ◽  
Therapy Response ◽  
Ease Of Use ◽  
Large Field ◽  
Age Related ◽  
System Usability Scale ◽  
Wide Range ◽  
Scale Scores ◽  
Mean Compliance

Access to affordable, objective and scalable biomarkers of brain function is needed to transform the healthcare burden of neuropsychiatric and neurodegenerative disease. Electroencephalography (EEG) recordings, both resting and in combination with targeted cognitive tasks, have demonstrated utility in tracking disease state and therapy response in a range of conditions from schizophrenia to Alzheimer's disease. But conventional methods of recording this data involve burdensome clinic visits, and behavioural tasks that are not effective in frequent repeated use. This paper aims to evaluate the technical and human-factors feasibility of gathering large-scale EEG using novel technology in the home environment with healthy adult users. In a large field study, 89 healthy adults aged 40–79 years volunteered to use the system at home for 12 weeks, 5 times/week, for 30 min/session. A 16-channel, dry-sensor, portable wireless headset recorded EEG while users played gamified cognitive and passive tasks through a tablet application, including tests of decision making, executive function and memory. Data was uploaded to cloud servers and remotely monitored via web-based dashboards. Seventy-eight participants completed the study, and high levels of adherence were maintained throughout across all age groups, with mean compliance over the 12-week period of 82% (4.1 sessions per week). Reported ease of use was also high with mean System Usability Scale scores of 78.7. Behavioural response measures (reaction time and accuracy) and EEG components elicited by gamified stimuli (P300, ERN, Pe and changes in power spectral density) were extracted from the data collected in home, across a wide range of ages, including older adult participants. Findings replicated well-known patterns of age-related change and demonstrated the feasibility of using low-burden, large-scale, longitudinal EEG measurement in community-based cohorts. This technology enables clinically relevant data to be recorded outside the lab/clinic, from which metrics underlying cognitive ageing could be extracted, opening the door to potential new ways of developing digital cognitive biomarkers for disorders affecting the brain.

scholarly journals Motivations for Virtual Community Participation in Social Commerce: Customers and Sellers in the Malay Lifestyle Blogging Community

2021 ◽  
Author(s):  
◽  
Syahida Hassan
Keyword(s):  
Social Support ◽  
Social Media ◽  
Large Scale ◽  
Virtual Communities ◽  
Virtual Community ◽  
Structured Interview ◽  
Ease Of Use ◽  
Social Commerce ◽  
Commercial Activities ◽  
The Social

<p>Although the field of social commerce has gained a lot of attention recently, there are many areas that still remain unexplored. A new phenomenon emerging within virtual communities is a blurring between social and commercial activities. To date, scholars in the social commerce literature have either focused on customers in the community or on medium to large scale businesses. There has been little research on social commerce communities which include micro-businesses despite their rapid growth in South East Asian countries.  This study explores a social commerce community of Malay lifestyle bloggers, who are a subset of the Malaysian blogosphere community. Bloggers begin by using the personal genre, some then move on to set up online businesses using their personal blogs as a platform. The characteristic of blogging’s ease of use means there are low barriers to starting a small business, merging blogging and commerce. This changes the nature of the community by bringing in a new relationship, as well as relationships between bloggers and readers, there are now also relationships between sellers and customers.  This study aims to understand the motivations for both sellers and customers, and how their relationships as bloggers and readers influence their participation in social commerce within the same community. To address the research objective, 20 sellers and 21 customers who also play a role as bloggers or readers were interviewed. In-depth interviews using laddering and semi-structured interview techniques were carried out to explore social commerce behaviour, the perceived consequences, and goals or values of participation. In addition, observation was also conducted on the platform used by the sellers. Data was coded using NVivo whilst the themes arising from the coding process were transformed into an implication matrix and hierarchical value map using Ladderux software.  This study found that strong ties within the community, influenced by homophily and the sense of virtual community, motivated the customers to participate in commercial activities in order to obtain their goals which included a sense of obligation, loyalty, satisfaction and self-esteem. The relationships influenced customers to trust each other, provide social support and made purchasing products more convenient. Sellers were influenced by the convenience of using social media and the social support provided by the customers which helped them to achieve their goals which are profit and business sustainability.  This study contributes to social commerce theory by highlighting an underexplored type of social commerce setting and addressing how trust can be transferred from social to commercial activities. The findings provide a useful insight for businesses, regardless of their size, to build an understanding of the need to create a good relationship with their customers. For macro-businesses, this model can be used to identify what is lacking in their social media marketing strategy.</p>

Performance of a Parallel Multi-Agent Simulation using Graphics Hardware

2014 ◽  
Vol 6 (4) ◽  
pp. 72-91
Author(s):  
Timothy W. C. Johnson ◽  
John R. Rankin
Keyword(s):  
Large Scale ◽  
Autonomous Agents ◽  
Graphics Hardware ◽  
Processing Unit ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Processing Power ◽  
Agent Simulation ◽  
Multi Agent ◽  
Graphical Processing

Large-scale Agent-Based Modelling and Simulation (ABMS) is a field of research that is becoming increasingly popular as researchers work to construct simulations at a higher level of complexity and realism than previously done. These systems can not only be difficult and time consuming to implement, but can also be constrained in their scope due to issues arising from a shortage of available processing power. This work simultaneously presents solutions to these two problems by demonstrating a model for ABMS that allows a developer to design their own simulation, which is then automatically converted into code capable of running on a mainstream Graphical Processing Unit (GPU). By harnessing the extra processing power afforded by the GPU this paper creates simulations that are capable of running in real-time with more autonomous agents than allowed by systems using traditional x86 processors.

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