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# Introduction

## A more technical introduction to the project

The framework can can create a virtual complex network with virtual agents that can interact with each other. This can be used for example to study the spread of an epidemic over this simulated network and compare it with a phenomenon in the real world. Agent-based simulation tools generally operate on a simple topology such as grids or lattices, but this framework goes beyond this limitation by providing support for simulation over complex topologies (i.e. any kind of non-regularly connected graph). In addition, this project is not limited to a static network, but also takes into account temporal networks, where processes can dynamically change the underlying network structure over time.

## A less technical introduction to the project

This document explains the creation of a new programming tool for simulating complex problems. The project allows people with a background in programming to simulate a situation, in which people, animals, computers, or abstract agents connect to each other arbitrarily. To give two concrete examples, it allows to simulate how a disease spreads in an human population, and it can simulate how connected computer servers that provide a service (such as Skype) can suddenly fail. It does this by creating virtual agents with a certain behaviour that are interconnected, and where behaviour and connections can change over time.

## An example output of a simple complex network simulation model

Imagine we take a social network of people, and one person has a disease. This person can now infect their friends with that disease. For this scenario we write a small model consisting of code for:

> - A network graph (e.g. a scale-free network)
> - An agent specification (e.g. spread disease on random neighbour)
> - Some output parameters (e.g. red colour for infected)
> - (optional) A network structure evolution (e.g. change links between agents)

then this project produces a visualisation of how the disease spreads in the network. (animated gif! - but it also produces static images)

and a plot showing the evolution of infected people:

The result data used for plotting and animation can of course also be used for integration in other analysis.

## What do I mean with Complex Networks and Agent-Based Simulations?

An agent-based simulation (ABS) is a system of multiple autonomous agents that interact with each other. We can think of these agents to for example represent people or animals, but they can also represent something more abstract. In an ABS, each agent has a state (e.g. alive or dead) and a defined behaviour (e.g. transmit a disease when infected). The simulation then lets these agents interact with each other, and looks at the overall change in agent states.

Complex networks are a type of graphs consisting of nodes and edges like any other graph, but they tend to represent something specific taken from the real world, such as people and friendship links, or the topology of a P2P network. Many different systems such as power grids, ecosystems, or the brain can be represented as a complex network.

## What is different in this package compared to normal agent-based simulations?

In basic agent-based simulations, the rules as to which agent is allowed to interact with which other agents are very simple: Either every agent can interact with every other agent, or agents are limited in their interaction with their neighbouring agents, as if agents were living on a chessboard (see e.g. for an overview of agent-based simulations). Clearly, these rules are not a very realistic scenario, so this project tries to address this issue by modeling the connections of the agents as a complex network, thus supporting *any* network topology underneath the simulation environment.

The main goal of this project hence was to implement a framework for agent-based simulations over complex networks, i.e. building support to run any kind of complex simulations based on a specific network topology. A secondary goal was to then create one or two simulation models representing a specific scenario.

Quick links to

Installation and Dependencies

Getting started with ComplexNetworkSim

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