scholarly journals Time-critical decentralised situational awareness in emergencies: an adversarial biosecurity scenario

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Jason Bassett ◽  
Niccolò Pescetelli ◽  
Alex Rutherford ◽  
Manuel Cebrian

AbstractCrises in a global setting of interdependencies call for time-critical coordinated responses. However, it is often the case that the mechanisms responsible for these actions do not agree across all their hierarchies. This can be roughly attributed to personal estimations of the situation and to social influence. An ensuing lack of consensus against crises can be dire and echo across entire populations. One such instance is the case of biosecurity threats. A particularly interesting class of threats lie within urban environments, which tend to fall within the scope of bad actors. With this work we aim to computationally contribute to the understanding of the dynamics of perceived danger formation among agents responsible for responding to ongoing biological attacks in urban settings. We assume this perception is a function of a personal estimation of local information about the danger and of social influence stemming from the agents in question framed in an agent-based model. The simulations point towards a high dependence of perceived dangers on the personal estimations of the agents. The conditions under which the perceived dangers deviate from the real ones are explored over a range of assumptions on personal measurements and several dispositions towards the influencing environment. The insight provided by these results at the individual and collective level set the tone for further investigation on such behavioural phenomena, providing a flexible computational framework addressing generic threats (true dangers) in a time-critical context.

2012 ◽  
Vol 15 (06) ◽  
pp. 1250077 ◽  
Author(s):  
DIRK VAN ROOY

This paper introduces a connectionist Agent-Based Model (cABM) that incorporates detailed, micro-level understanding of social influence processes derived from laboratory studies and that aims to contextualize these processes in such a way that it becomes possible to model multidirectional, dynamic influences in extended social networks. At the micro-level, agent processes are simulated by recurrent auto-associative networks, an architecture that has a proven ability to simulate a variety of individual psychological and memory processes [D. Van Rooy, F. Van Overwalle, T. Vanhoomissen, C. Labiouse and R. French, Psychol. Rev. 110, 536 (2003)]. At the macro-level, these individual networks are combined into a "community of networks" so that they can exchange their individual information with each other by transmitting information on the same concepts from one net to another. This essentially creates a network structure that reflects a social system in which (a collection of) nodes represent individual agents and the links between agents the mutual social influences that connect them [B. Hazlehurst, and E. Hutchins, Lang. Cogn. Process. 13, 373 (1998)]. The network structure itself is dynamic and shaped by the interactions between the individual agents through simple processes of social adaptation. Through simulations, the cABM generates a number of novel predictions that broadly address three main issues: (1) the consequences of the interaction between multiple sources and targets of social influence (2) the dynamic development of social influence over time and (3) collective and individual opinion trajectories over time. Some of the predictions regarding individual level processes have been tested and confirmed in laboratory experiments. In a extensive research program, data is currently being collected from real groups that will allow validating the predictions of cABM regarding aggregate outcomes.


2021 ◽  
Vol 11 (5) ◽  
pp. 2057
Author(s):  
Abdallah Namoun ◽  
Ali Tufail ◽  
Nikolay Mehandjiev ◽  
Ahmed Alrehaili ◽  
Javad Akhlaghinia ◽  
...  

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.


2017 ◽  
Vol 4 (8) ◽  
pp. 170344 ◽  
Author(s):  
Thiago Mosqueiro ◽  
Chelsea Cook ◽  
Ramon Huerta ◽  
Jürgen Gadau ◽  
Brian Smith ◽  
...  

Variation in behaviour among group members often impacts collective outcomes. Individuals may vary both in the task that they perform and in the persistence with which they perform each task. Although both the distribution of individuals among tasks and differences among individuals in behavioural persistence can each impact collective behaviour, we do not know if and how they jointly affect collective outcomes. Here, we use a detailed computational model to examine the joint impact of colony-level distribution among tasks and behavioural persistence of individuals, specifically their fidelity to particular resource sites, on the collective trade-off between exploring for new resources and exploiting familiar ones. We developed an agent-based model of foraging honeybees, parametrized by data from five colonies, in which we simulated scouts, who search the environment for new resources, and individuals who are recruited by the scouts to the newly found resources, i.e. recruits. We varied the persistence of returning to a particular food source of both scouts and recruits and found that, for each value of persistence, there is a different optimal ratio of scouts to recruits that maximizes resource collection by the colony. Furthermore, changes to the persistence of scouts induced opposite effects from changes to the persistence of recruits on the collective foraging of the colony. The proportion of scouts that resulted in the most resources collected by the colony decreased as the persistence of recruits increased. However, this optimal proportion of scouts increased as the persistence of scouts increased. Thus, behavioural persistence and task participation can interact to impact a colony's collective behaviour in orthogonal directions. Our work provides new insights and generates new hypotheses into how variations in behaviour at both the individual and colony levels jointly impact the trade-off between exploring for new resources and exploiting familiar ones.


2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Jennifer Olsen

IntroductionEpiCore draws on the knowledge of a global community of human,animal, and environmental health professionals to verify informationon disease outbreaks in their geographic regions. By using innovativesurveillance techniques and crowdsourcing these experts, EpiCoreenables faster global outbreak detection, verification, and reporting.MethodsThrough a secure online platform, members are able to easily andquickly provide local information to expedite outbreak verification.EpiCore volunteer applications are vetted to ensure that they possessthe public health and epidemiologic expertise necessary to contributeto the platform.ResultsEpiCore currently has over 1600 members that span 135 countries.During the first 8 months of EpiCore’s launch, 172 requests forinformation to volunteers have been posted with an average responserate of over 80%.ConclusionsWith its geographical distribution of members and high responserate, EpiCore is poised to enable the world to verify potential outbreaksignals faster. By improving situational awareness, de-escalatingrumors or false information, and corroborating using other existingsources, EpiCore is able to reduce the signal to noise ratio in diseasesurveillance. Hence, by detecting and verifying outbreaks faster,health officials can generate early responses that can curb epidemicsand save lives.


2019 ◽  
Vol 6 (1) ◽  
pp. 85-100
Author(s):  
Madani Hatta ◽  
Fenny Marietza ◽  
Rewa Yoke Desthomson

This study aims to determine the influence of utilization intention and use accounting software for individual performance by using a model unifiedtheory of acceptance and use of technology (UTAUT) consisted of performance expectation, effort expectation, social influence, facilitating conditions, the intention of the use of accounting software, the useof accounting software, and the individual performance. The sample in this study were 61 employees of the banking company in the city of Bengkulu who use accounting software in their working activity. The results showed that the performance expectation has significant positive influence to intention utilization accounting software, effort expectation has  significant positive influence to the intention utilization accounting software, social influence has significant positive influence to the use of accounting software intention, facilitating condition has significant positive influence to the use of accounting software, accounting software utilization intention has significant positive influence to the use of accounting software and the use of accounting software has positive influence to the performance of the individual.Key words : Performance Expectation, Effort Expectation, Social Influence, The Facilitating Conditions, Intention Utilization, Use of Accounting Software, UTAUT.


Author(s):  
Gabriel Franklin ◽  
Tibérius O. Bonates

This chapter describes an agent-based simulation of an incentive mechanism for scientific production. In the proposed framework, a central agency is responsible for devising and enforcing a policy consisting of performance-based incentives in an attempt to induce a global positive behavior of a group of researchers, in terms of number and type of scientific publications. The macro-level incentive mechanism triggers micro-level actions that, once intensified by social interactions, lead to certain patterns of behavior from individual agents (researchers). Positive reinforcement from receiving incentives (as well as negative reinforcement from not receiving them) shape the behavior of agents in the course of the simulation. The authors show, by means of computational experiments, that a policy devised to act at the individual level might induce a single global behavior that can, depending on the values of certain parameters, be distinct from the original target and have an overall negative effect. The agent-based simulation provides an objective way of assessing the quantitative effect that different policies might induce on the behavior of individual researchers when it comes to their preferences regarding scientific publications.


2019 ◽  
pp. 1-20
Author(s):  
Ermanno Catullo ◽  
Federico Giri ◽  
Mauro Gallegati

The paper presents an agent-based model reproducing a stylized credit network that evolves endogenously through the individual choices of firms and banks. We introduce in this framework a financial stability authority in order to test the effects of different prudential policy measures designed to improve the resilience of the economic system. Simulations show that a combination of micro- and macroprudential policies reduces systemic risk but at the cost of increasing banks’ capital volatility. Moreover, the agent-based methodology allows us to implement an alternative meso regulatory framework that takes into consideration the connections between firms and banks. This policy targets only the more connected banks, increasing their capital requirement in order to reduce the diffusion of local shocks. Our results support the idea that the mesoprudential policy is able to reduce systemic risk without affecting the stability of banks’ capital structure.


2011 ◽  
pp. 3321-3338
Author(s):  
Vasco Furtado ◽  
Eurico Vasconcelos

In this work we will describe EGA (educational geosimulation architecture), an architecture for the development of pedagogical tools for training in urban activities based on MABS (multi-agent based simulation), GIS (geographic information systems), and ITS (intelligent tutoring systems). EGA came as a proposal for the lack of appropriate tools for the training of urban activities with high risk and/or high cost. As a case study, EGA was used for the development of a training tool for the area of public safety, the ExpertCop system. ExpertCop is a geosimulator of criminal dynamics in urban environments that aims to train police officers in the activity of preventive policing allocation. ExpertCop intends to induce students to reflect about their actions regarding resources allocation and to understand the relationship between preventive policing and crime.


Author(s):  
Ben Tse

This chapter presents an architecture, or general framework, for an agent-based electronic health record system (ABEHRS) to provide health information access and retrieval among different medical services facilities. The agent system’s behaviors are analyzed using the simulation approach and the mathematical modeling approach. The key concept promoted by ABEHRS is to allow patient health records to autonomously move through the computer network uniting scattered and distributed data into one consistent and complete data set or patient health record. ABEHRS is an example of multi-agent swarm system, which is composed of many simple agents and a system that is able to self-organize. The ultimate goal is that the reader should appreciate the benefits of using mobile agents and the importance of studying agent behaviors at the system level and at the individual level.


Author(s):  
Harshika Singh ◽  
Gaetano Cascini ◽  
Hernan Casakin ◽  
Vishal Singh

AbstractThe dynamics of design teams play a critical role in product development, mainly in the early phases of the process. This paper presents a conceptual framework of a computational model about how cognitive and social features of a design team affect the quality of the produced design outcomes. The framework is based on various cognitive and social theories grounded in literature. Agent-Based Modelling (ABM) is used as a tool to evaluate the impact of design process organization and team dynamics on the design outcome. The model describes key research parameters, including dependent, independent, and intermediates. The independent parameters include: duration of a session, number of times a session is repeated, design task and team characteristics such as size, structure, old and new members. Intermediates include: features of team members (experience, learning abilities, and importance in the team) and social influence. The dependent parameter is the task outcome, represented by creativity and accuracy. The paper aims at laying the computational foundations for validating the proposed model in the future.


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