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ACIT4610 - Evolutionary AI > Lecture 03 - Network models > Flashcards

Lecture 03 - Network models Flashcards

1
Q

Networks

What is another name for a network?

A

A graph

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2
Q

Networks

What does a network consist of?

A

Nodes/vertices and edges

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3
Q

Networks

What is a neighbour?

A

If nodes A and B are connected with an edge, they are neighbours.

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4
Q

Networks

What are the two most common ways to represent networks in a computer?

A
  • Adjacency matrix
  • Adjacency list
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5
Q

Networks

What is an adjacency matrix?

A

A matrix of m * m elements which shows how each node is connected to all other nodes.

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6
Q

Networks

What is an adjacency list?

A

A dictionary mapping nodes to a list of which other nodes they’re connected to. Python annotation: dict[str, list[str]]

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7
Q

Networks

What is this?

A

An adjacency matrix

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8
Q

Networks

What is this?

A

An adjacency list

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9
Q

Networks

What is the degree of a node?

A

The number of edges connected to it.

For directed nodes, there’s a difference between “indegree” and “outdegree” as well

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10
Q

Networks

What’s the typical way of writing the node’s degree?

A

deg(i), with i being the i-th node.

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11
Q

Networks

What is a walk?

A

A list of edges that are sequentially connected to form a continuous route in a network.

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12
Q

Networks

What is a trail?

A

A walk that doesn’t go through any edge more than once.

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13
Q

Networks

What is a path?

A

A walk that doesn’t go through any node more than once.

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14
Q

Networks

What is a cycle?

A

A walk that starts and ends at the same node, without going through any node more than once.

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15
Q

Networks

What is this a description of?

“A list of edges that are sequentially connected to form a continuous route in a network.”

A

A walk

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16
Q

Networks

What is this a description of?

“A walk that doesn’t go through any edge more than once.”

A

A trail

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17
Q

Networks

What is this a description of?

“A walk that doesn’t go through any node more than once.”

A

A path

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18
Q

Networks

What is this a description of?

“A walk that starts and ends at the same node, without going through any node more than once.”

A

A cycle

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19
Q

Networks

What is a subgraph?

A

A part of the graph.

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20
Q

Networks

What is a connected graph?

A

A graph in which a path exists between any pair of nodes.

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21
Q

Networks

What is a connected component?

A

A subgraph of a graph that is connected within itself, but not to the rest of the graph.

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22
Q

Networks

What is this a description of?

“A graph in which a path exists between any pair of nodes.”

A

A connected graph

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23
Q

Networks

What is the name of a subgraph that is connected within itself, but not to the rest of the graph.

A

A connected component

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24
Q

Networks

What is this a description of?

“A part of the graph.”

A

A subgraph

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25
Q

Networks

What is a complete graph?

A

A graph in which any pair of nodes are connected

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26
Q

Networks

What is a Regular graph?

A

A graph in which all nodes have the same degree. Every complete graph is regular.

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27
Q

Networks

What is a Bipartite (n-partite) graph ?

A

A graph whose nodes can be divided into two (or n) groups so that no edge connects nodes between the groups. The groups can be connected within themselves.

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28
Q

Networks

What is a Tree graph?

A

A graph in which there is no cycle. A graph made of multiple trees is called a forest graph. Every tree or forest graph is bipartite.

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29
Q

Networks

What is a Planar graph?

A

A graph that can be graphically drawn in a two-dimensional plane with no edge crossings. Every tree or forest graph is planar.

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30
Q

Networks

What is this an example of?

“A graph in which any pair of nodes are connected”

A

Complete graph

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31
Q

Networks

What is this an example of?

“A graph in which all nodes have the same degree.”

A

Regular graph

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32
Q

Networks

What is this an example of?

“A graph whose nodes can be divided into two (or n) groups so that no edge connects nodes within each group”

A

Bipartite (n-partite) graph

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33
Q

Networks

What is this an example of?

“A graph in which there is no cycle.”

A

Tree graph

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34
Q

Networks

What is this an example of?

“A graph that can be graphically drawn in a two-dimensional plane with no edge crossings.”

A

Planar graph

35
Q

Networks

What is this an example of?

A

Complete graphs

36
Q

Networks

What is this an example of?

A

Regular graphs

37
Q

Networks

What is this an example of?

A

Bipartite (n-partite) graphs

38
Q

Networks

What is this an example of?

A

Tree graphs

39
Q

Networks

What is this an example of?

A

Planar graphs

40
Q

Networks

What is an undirected edge?

A

An edge that is connected in both ways to the node, like a pavement.

41
Q

Networks

What is a directed edge?

A

An edge that is only connected in one direction, like a one-way street.

42
Q

Networks

What’s an unweighted edge?

A

An edge that has no attached weight/cost. Adjacency matrices have just 0 or 1 as elements.

43
Q

Networks

What is a weighted edge?

A

An edge with an attached weight/cost, usually positive values, like connection strength or distance.

44
Q

Networks

What is node strength?

A

The sum of the weights of the edges attached to the node.

45
Q

Networks

What’s special about the adjacency matrix of an undirected graph?

A

It’s symmetric.

46
Q

Networks

Can two nodes share multiple edges?

A

Yes, nodes can have multiple edge, directed or undirected, with different weights.

47
Q

Networks

What is a simple loop?

A

An edge that starts and ends at the same node.

48
Q

Networks

What’s an edge called when it has no direction.

A

An undirected edge.

49
Q

Networks

What’s an edge called when it has a direction?

A

A directed edge.

50
Q

Networks

What’s an edge called when it has a cost/weight?

A

A weighted edge.

51
Q

Networks

What’s an edge called when it doesn’t have a cost/weight?

A

An unweighted edge.

52
Q

Networks

What is the sum of all edge weights for a node called?

A

The node strength.

53
Q

Networks

If you have an adjacency matrix that’s symmetric, what’s that type of network called?

A

An undirected network.

54
Q

Networks

What do you call an edge that starts and ends at the same node?

A

A simple loop.

55
Q

Networks

What is a simple graph? (4)

A

A graph that doesn’t contain directed, weighted or multiple edges, and has no self-loops.

56
Q

Networks

What do you call a graph that doesn’t contain directed, weighted or multiple edges, and has no self-loops.

A

A simple graph

57
Q

Networks

What is a multigraph?

A

A graph that may contain multiple edges and both (un)directed edges. Some definitions include self-loops.

58
Q

Networks

What do you call a graph that may contain multiple edges and both (un)directed edges. Some definitions include self-loops.

A

A multigraph.

59
Q

Networks

What is a hyperedge?

A

An edge that can connect more than two nodes.

60
Q

Networks

What do you call an edge that can connect more than two nodes?

A

A hyperedge

61
Q

Networks

What are models for “dynamics ON networks”?

A

Models that deal with how nodes in a network change over time. The network topology is fixed/unchanging.

62
Q

Networks

What are models that deal with nodes changing, but fixed network topologies?

A

Models for “dynamics ON networks”

63
Q

Networks

What are models for “dynamics OF networks”?

A

Models that deal with changes to the network topology only.

64
Q

Networks

What are models that deal with changes to the network topology only called?

A

Models for “dynamics OF networks”

65
Q

Networks

What are models for “adaptive networks”?

A

Models that describe the co-evolution of both “dynamics on” and “dynamics of” networks.

66
Q

Networks

What are models that describe the co-evolution both “dynamics on” and “dynamics of” networks called?

A

Models for “Adaptive networks”.

67
Q

Networks

How does the “majority rule model” work?

A
  • Initialize a population with random states (e.g. 0 or 1)
  • During the update step, each individual changes to the majority of its neighbours.
68
Q

Networks

How is the “voter model” different from the “majority rule model”?

A

In the voter model, a single node pair of connected nodes is chosen at a time. Between them, a vote is transferred.

69
Q

Networks

What are some variations of the “voter model”? (ORE)

A
  • Original
  • Reversed
  • Edge-based
70
Q

Networks

In the voter model, how does the “original variation” work?

A

A listener is chosen, and then a speaker is chosen from the listener’s neighbourhood.

71
Q

Networks

In the voter model, how does the “reversed variation” work?

A

A speaker is chosen, then a random listener is chosen fro the speaker’s neighbourhood.

72
Q

Networks

What is a different name for the voter model “original variation”?

A

Push

73
Q

Networks

What is a different name for the voter model “reversed variation”?

A

Pull

74
Q

Networks

In the voter model, how does the “edge-based variation” work?

A

Edges are chosen at random, then the connected nodes are selected as speaker and listener, respectively.

75
Q

Networks

How does the “Epidemic model” work? (SIR model)

A
  • Initialize nodes as either susceptible (S) or infected (I).
  • I can infect S with some prob.
  • I can recover with some prob to either state recovered (R) or S.
76
Q

Networks

How does the “Diffusion model” work?

A

During updates, nodes are affected by all their neighbours. Think heat transfer.

N_i.state += C*sum(N_i.neighbors.state) / deg(N_i)

77
Q

Networks

What are small-world network?

A

Networks with short paths among all nodes, despite not being a complete graph.

78
Q

Networks

What are networks with short paths among all nodes called?

A

Small-world networks.

79
Q

Networks

What are scale-free networks?

A

Networks where the distribution of edges between networks follow a power law distribution; that is, most nodes have few neighbors, but some nodes are very central and have many neighbors.

80
Q

Networks

What do you call a network where most nodes have few neighbors, but a few number of nodes have many neighbors?

A

A scale-free network.

81
Q

Networks

What is homophily?

A

An empirically observed sociological fact that people tend to connect those who are similar to themselves

82
Q

Networks

Can walks have loops?

A

Yes

83
Q

Networks

Can trails have loops?

A

No

84
Q

Networks

Can paths have loops?

A

No

ACIT4610 - Evolutionary AI (11 decks)

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