Related papers: Agent-based Simulation Model and Deep Learning Tec…
Autonomous systems often operate in environments where the behavior of multiple agents is coordinated by a shared global state. Reliable estimation of the global state is thus critical for successfully operating in a multi-agent setting. We…
The COVID-19 pandemic has affected countries across the world, demanding drastic public health policies to mitigate the spread of infection, leading to economic crisis as a collateral damage. In this work, we investigated the impact of…
Agent-based modelling (ABM) is a facet of wider Multi-Agent Systems (MAS) research that explores the collective behaviour of individual `agents', and the implications that their behaviour and interactions have for wider systemic behaviour.…
Agent-based model (ABM) are a kind of computer model that makes it possible to simulate a set of autonomous interacting programs called agents in a shared virtual environment. Among other application field, it has been commonly used to…
The practical utility of agent-based models in decision-making relies on their capacity to accurately replicate populations while seamlessly integrating real-world data streams. Yet, the incorporation of such data poses significant…
Agent-based simulations have been used in modeling transportation systems for traffic management and passenger flows. In this work, we hope to shed light on the complex factors that influence transportation mode decisions within developing…
Violence against women occurs predominantly in the family and domestic context. The COVID-19 pandemic led Brazil to recommend and, at times, impose social distancing, with the partial closure of economic activities, schools, and…
This study examined a simulated confined space modelled as a hospital waiting area, where people who could have underlying conditions congregate and mix with potentially infectious individuals. It further investigated the impact of the…
The way of analyzing, designing and building of real-time projects has been changed due to the rapid growth of internet, mobile technologies and intelligent applications. Most of these applications are intelligent, tiny and distributed…
COVID-19 has resulted in a worldwide pandemic, leading to "lockdown" policies and social distancing. The pandemic has profoundly changed the world. Traditional methods for observing these historical events are difficult because sending…
The number of confirmed cases of COVID-19 is often used as a proxy for the actual number of ground truth COVID-19 infected cases in both public discourse and policy making. However, the number of confirmed cases depends on the testing…
The ongoing coronavirus disease 2019 (COVID-19) pandemic has wreaked havoc worldwide with millions of lives claimed, human travel restricted and economic development halted. Leveraging city-level mobility and case data, our analysis shows…
Computational disease modeling plays a crucial role in understanding and controlling the transmission of infectious diseases. While agent-based models (ABMs) provide detailed insights into individual dynamics, accurately replicating human…
The SARS-CoV-2 infectious outbreak has rapidly spread across the globe and precipitated varying policies to effectuate physical distancing to ameliorate its impact. In this study, we propose a new hybrid machine learning model, SIRNet, for…
One of the most notable global transportation trends is the accelerated pace of development in vehicle automation technologies. Uncertainty surrounds the future of automated mobility as there is no clear consensus on potential adoption…
Accurate forecasts of COVID-19 is central to resource management and building strategies to deal with the epidemic. We propose a heterogeneous infection rate model with human mobility for epidemic modeling, a preliminary version of which we…
Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of the agent-based models from…
During the COVID-19 pandemic, a large variance of incidence rates on local level, e.g. cities and districts, within one country has been observed, while the same non-pharmaceutical measures have been taken to control the spread of the…
The short-term economic consequences of the critical measures employed to curb the transmission of Covid-19 are all too familiar, but the consequences of isolation and loneliness resulting from those measures on the mental well-being of the…
Transportation and traffic are currently undergoing a rapid increase in terms of both scale and complexity. At the same time, an increasing share of traffic participants are being transformed into agents driven or supported by artificial…