Network Science Quiz

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Questions and Answers

What is the primary function of the neural network?

To supply energy to modern technology

To facilitate communication between devices

To describe the connections between neurons (correct)

To maintain trade of goods and services

Which of the following best describes the role of social networks?

They are responsible for epidemic control.

They represent the fabric of society and influence behavior. (correct)

They determine the exchange of energy resources.

They connect communication devices for modern technology.

What type of network is primarily concerned with exchanging goods and services?

Neural network

Power grid

Communication network

Trade network (correct)

In the context of networks, what do nodes represent?

Entities such as genes or neurons Signup and view all the answers

What is the relationship represented by links in a network?

The relations such as regulation or kinship Signup and view all the answers

Which aspect is NOT mentioned as a focus of network science?

Psychology Signup and view all the answers

In the Seven Bridges of Königsberg problem, what was the main objective?

To cross each bridge once and only once Signup and view all the answers

How is the strength of a node related to its effectiveness in a network?

It is influenced by the number of connections it has. Signup and view all the answers

What does betweenness in a network indicate?

The number of shortest paths passing through a node or edge Signup and view all the answers

What is the purpose of centrality measures in complex networks?

To identify the core entities and relations within the network Signup and view all the answers

How do the centrality measures help in studying networks?

By evaluating resilience to node or link removal Signup and view all the answers

Which of the following models is associated with the Small World phenomenon?

Watts-Strogatz model Signup and view all the answers

What type of network is described as having hubs with high connectivity?

Scale-Free Network Signup and view all the answers

Which selection method is used in the setup of the MuGA tool?

Tournament Selection Signup and view all the answers

What parameter change is suggested for running the algorithm on a small problem?

Reduce the number of generations to 40 Signup and view all the answers

Which type of mutation is selected in the MuGA configuration?

Real-valued Gaussian Mutation Signup and view all the answers

What is the purpose of changing the view in the Main Population window?

To visualize the population dynamics Signup and view all the answers

What happens when the stop criteria are met during the algorithm's execution?

The algorithm halts and displays results Signup and view all the answers

Which of the following strategies is suggested to experiment with different setups in MuGA?

Vary the probability of mutation while changing crossover rates Signup and view all the answers

In the context of MuGA, what is indicated by ‘bi-stable’ states?

The population fluctuates between two optimal states Signup and view all the answers

What must be done after selecting 'real coded' and 'F3_Shifted_Rosenbrock' in the Setup?

Change 'Parameters' to the number of variables Signup and view all the answers

What does each node in the large graphs represent in the simulations?

A specific bacteria population Signup and view all the answers

What process is involved in the network simulation?

Edge list creation Signup and view all the answers

How many generations are simulations run for in the experimental setup?

2500 generations Signup and view all the answers

What does the Simpsons Index of Diversity (SID) measure in the context of the simulations?

Diversity of populations Signup and view all the answers

What is the significance of the 'exchange between nodes' in the simulation process?

It occurs after a cycle of evolutions Signup and view all the answers

Which of the following is NOT included in the simulation process for each node?

Environmental conditions Signup and view all the answers

What does the 'recombination rate' refer to in the context of the individual profiles in simulation?

Frequency of allele mixing events Signup and view all the answers

Which computational model is mentioned for handling the data in the simulations?

GraphX Signup and view all the answers

Which of the following platforms is NOT mentioned as a service to run Jupyter notebooks in the cloud?

AWS Notebooks Signup and view all the answers

What is one of the main challenges in validating methods used for studying pathogen populations?

Small size of accessible real pathogen population samples Signup and view all the answers

Which question addresses the diversity of bacterial populations in relation to mixing?

Are all populations well-mixed? Signup and view all the answers

Which service can be used to run Jupyter notebooks that provides a collaborative environment specifically for data science?

Datalore Signup and view all the answers

What evolutionary model is mentioned as a basis for explaining the population structure of human pathogens?

Neutral mutational drift model Signup and view all the answers

What aspect of bacterial populations is questioned regarding the absence of selection phenomena?

Genetic diversity Signup and view all the answers

Among the following, which service provides an online code execution environment specifically tailored for interactive machine learning?

Google Colab Signup and view all the answers

Which question reflects a consideration for host contact networks' effects on bacterial populations?

What is the impact of host contact network topologies? Signup and view all the answers

What is a primary characteristic of communities in a network?

Communities have many internal links among their nodes. Signup and view all the answers

Which of the following is NOT a common method for community detection in networks?

Frequency analysis Signup and view all the answers

What does link betweenness measure in a network?

The importance of a link based on how many shortest paths pass through it. Signup and view all the answers

What is the significance of modularity in community detection?

It helps to measure the density of connections within a community compared to the expected density. Signup and view all the answers

Which clustering method focuses on identifying partitions with high internal connectivity?

Stochastic block model Signup and view all the answers

Which tool is specifically designed for visualizing and analyzing networks?

Gephi Signup and view all the answers

In terms of community detection, what is a defining characteristic of algorithms based on hierarchical clustering?

They do not require prior knowledge of the number of communities. Signup and view all the answers

What is the relationship between internal and external links in a well-separated community?

There are many internal links and few external links. Signup and view all the answers

Study Notes

Genetic Algorithms - TP Genetic Algorithms

The MUGA tool can be downloaded from Moodle
Unzip the downloaded archive
Open the "MUGA_12_full.jar" file using java
To setup the tool, go to "Select Problem"
Choose "real coded" and "F3_Shifted Rosenbrock"
Change "Parameters" to 2
Select "Simple Population"
Press "Set Parameters"

Genetic Algorithms Tool Setup

Select the problem from the available options
Choose "real coded" and "F4_Shifted_Rastrigin" as a problem example
Change the number of parameters to 2
Select "Simple Population" as the population model
Click "Set Parameters"

Genetic Algorithm Implementation Steps

The user should go back to the MuGA-Home page
Then they should click on the Run Genetic Algorithm tab
Change the default values for the criteria and the population to appropriate values for a small problem
The population should move to the plot window
If delay >0, increase the delay to see the population moving faster
Use the 'setup Statistics' tab to add graphs from the data of several trials
To step through each stage of the algorithm click start
The two new windows that appear contain the offspring population and the best value plot

Questions and Investigations

Vary the Rosenbrock and Rastrigin functions with different numbers of variables
Focus on mutation probability and selection parameters (tournament size, k value) in the experimentation
Explore crossover mechanisms, considering the absence of mutation
Evaluate the fitness of the best individual and the number of generations it takes to obtain it in different iterations
Analyze how mutation rate and selection pressure influence convergence in the algorithm
Investigate the robustness of the algorithm to changes in the fitness landscape
Test the algorithm on the Shifted Sphere, Griewank, and Ackley functions

Swarms

Swarms are self-organised multi-agent systems with emergent collective behaviour
A key example of swarming behaviour is bird flocking or fish schooling, governed by simple rules.
Rules for bird flocking/fish schooling include:
- Moving away from neighbors if too close
- Moving closer to neighbors if too far away
- Aligning with the average orientation of neighbors.
Parameters affect swarming behaviors, including approaching, separating, and turning ratios.
Swarm behavior results from simple individual rules.
Social simulation is based on individuals that are allowed to be different types, but prefer to be surrounded by individuals of similar type. Individuals may move to a location if less than a certain percentage of neighbors have their own color.

Self-Organisation (SO)

SO systems are self-organised multi-agent systems (swarms) with emergent collective behaviour.
SO properties are:
- No external control.
- Increase in order after perturbations.
- Adaptability.
- Interaction.
- Asynchronism.
SO mechanisms are:
Positive feedback (amplifying an effect, examples include: ants recruiting for a food source).
Negative feedback (stabilizing an effect, examples include: the end of a food source).
Random fluctuations (noise, examples include: a lost ant may explore).

Ant Colony Optimisation (ACO)

ACO is a swarm intelligence algorithm
Problem: Travelling Salesperson Problem (TSP)
Find the minimum route visiting each city only once
In Euclidean space: Distance between cities $d_{ij} = [(x_i - x_j)^2 + (y_i - y_j)^2]^{1/2}$
J_i is a set of cities to visit by ant k, in city i
Initially, all cities except the starting city (i) in the list

Particle Swarm Optimisation (PSO)

PSO was proposed in 1995 by Kennedy and Eberhart
It is a physical particles model inspired in social-psychological theory
Each particle represents a multi-dimensional point in search space
It has position and velocity
It is influenced by own previous behaviour and neighbours’ success

Swarm Optimisation Analysis

ACO and PSO are models of self-organisation
Both are robust tools for optimisation
PSO models are decentralised and have local interaction
ACO models are decentralised but require global information

Portuguese Studies of Cooperation

Questions concerning conditions that allow cooperation to emerge spontaneously within societies composed of selfish agents, with or without a central authority.
Goal is to develop mechanisms for encouraging cooperation in both real and artificial systems to better understand the behaviour of such systems in nature (e.g., birds flocking).
The analysis from the theory of natural selection points out that cooperative behaviour could be disadvantageous. However, cooperative behaviours exist in nature.
Examples of cooperative behaviour in nature include alarm calls by birds and monkeys, food sharing in bats.

Game Theory

Game theory models interactions as games, considering that players are rational.
Games are represented by payoff matrices.
Nash Equilibrium (NE) defines a combination of strategies where no player gains advantage by changing their strategy unilaterally. NE can involve mixed strategies.

Prisoner's Dilemma

A payoff matrix is used to explain the prisoner's dilemma
Nash Equilibrium is (T, T) - suggesting that cooperation is not rational in the one-shot game.
However, if the game is repeated, cooperation may be more beneficial.

Snowdrift Game

A payoff matrix is used to explain the snowdrift game
Nash Equilibria are (C, T), (T, C), and a combination of mixed strategies that depend on the relative values of the payoffs.
Pure strategies usually suggest the opposite strategy than the other participant
A strategy of opposing the other players strategy in a repeated game may result in better payoffs for both participants.

Iterated Prisoner's Dilemma

Iterated Prisoner's Dilemma (IPD) describes a game played multiple times by players with memory of previous interactions.
The rational choice for repeated games is to not cooperate.
However, a strategy of mutual cooperation, like TIT-FOR-TAT, can succeed in IPD.

Axelrod's Tournament

Researchers submitted strategies to play iterated prisoner's dilemma,
The simplest strategy, TIT-FOR-TAT, usually performed the best.

TIT-FOR-TAT

The TIT-FOR-TAT strategy initially cooperates and then mirrors the previous move of its opponent.
Success depends on:
- Not being the first to defect.
- Immediate retaliation for defections.
- Quickly forgetting previous defections.
- Possibility of future interactions among players.

Evolutionary Game Theory

Evolutionary game theory studies cooperation from an evolutionary perspective, including how adaptive strategies spread in a population and how the population adapts to changes in strategies using the principle of replication by comparing fitness.
It doesn't assume rational agents, but instead fitness describes how adaptive an agent is in different situations.
The evolution of strategies can be by:
- Stability analysis
- Explicit populations and their dynamic properties.

Evolutionary Stable Strategy (ESS)

A strategy is an evolutionarily stable strategy (ESS) if a population with that strategy cannot be invaded by a rare mutant adopting a different strategy.

Other Ways to Achieve Cooperation

Cooperation can also come from:
- Altruism (especially for biological connections)
- Grouping (allows like entities to interact frequently)
- Explicit population simulations and applying the replication equation

Replication Equation

Used in the explicit population simulations of strategies. It's used to compare the evolutionary success of different strategies or groups of agents in the same environment.

Symmetric Games

In symmetric two-player games, each player performs the same role.
The payoff matrix is represented by 911, 912, 921, 922

Numerical Results

Shows how degree centrality affects the average proposal as the value of $α$ changes
Investigates how $α$ and $M$ values influence the average payoff
Analyzes the $M$ parameter impact on Lorenz curves, with various choices of $α$

Other Aspects of SO in Peer Production

Modularity
Evolution
Hierarchy Formation
Size and Free-Riding

Network Types

Regular networks
Small-world networks
Random networks
Scale-free networks

Community Detection

An important method for uncovering the organization of networks
Features include:
- Highly connected internal nodes
- Fewer links between different communities

Graph Theory

Studying networks using graphs
Nodes are entities like genes, neurons, etc
Edges describe relations (kin ship, similarity, co-occurrence)
Relations can be:
- (non) reciprocal
- weighted
- temporal
Node strength is related to the number of connections it has.

Data Collection

Data from several medical and political sources
Networks of disease are used to represent human systems.
Methods from network science are used to model epidemics.

Information Dynamics

Information dynamics in Internet-mediated prostitution networks
Networks of about 6,000 sex workers and approximately 10,000 buyers
The links represent encounters between buyers and sex workers, and information is exchanged via online posts
This is an example of a bipartite model
The model can be used to understand disease transmission, specifically in the context of gonorrhea and HIV.

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Description

Test your knowledge on the fundamentals of network science, including neural networks, social networks, and the characteristics of various types of networks. This quiz covers critical concepts such as nodes, links, centrality measures, and the Small World phenomenon. Perfect for students studying network theory and related fields.