Jun 22, 2022 · Abstract: We present a novel graph neural network we call AgentNet, which is designed specifically for graph-level tasks. AgentNet is inspired by sublinear algorithms, …

Agent-based models (ABM)56, 65, 67, 112 represent another class of simulation wherein each human of a population is modeled as a distinct entity or agent that is attributed with traits and …

Dec 5, 2018 · Directed acyclic graph (DAG)-based regression modelling directs greatest focus towards modelling mean structures (i.e. ‘fixed’ effects), whereas simulation approaches …

Here I describe some design choices and present some practical examples of an application that uses a graph database with an ABM that sim-ulates the social processes that generate the …

An agent-based model (ABM) is a computational model for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) in …

In agent-based modeling, we construct a model by defining a set of agents and the rules by which those agents interact. There are many good software packages for agent-based modeling, …

Nov 1, 2022 · Agent-based modelling (ABM) has gained momentum as a simulation technique. We systematically review the application of the ABM paradigm in 86 mobility transition studies. …

Directed acyclic graph (DAG)-based regression modelling directs greatest focus towards modelling mean structures (i.e. ‘fixed’ effects), whereas simulation approaches embrace …

In agent-based models, individual interactions are simulated to generate social patterns of all kinds, including relationships that can then be analyzed by social network analysis. This …

Agents.jl is a pure Julia framework for agent-based modeling (ABM): a computational simulation methodology where autonomous agents react to their environment (including other agents) …