Swarm Intelligence

Question 1

One property of a swarm is each member’s inability to do a task by itself, but…

Answer 1

It can do the same task easily as a swarm

Question 2

The ability to do a task that a member could not do otherwise is called…

Answer 2

An emergent property of the swarm

Question 3

Each element of a swarm has…

Answer 3

A simple behaviour, and a set of rules for interacting with other members and the environment

Question 4

Ant Colony Optimisation is an evolutionary algorithm inspired by ants, used for the task of…

Answer 4

Finding the shortest path/optimisation of a task (both are technically true)

Question 5

Stimergy is a phenomenon we observe in nature, such that…

Answer 5

Animals communicate via interaction with the environment

Question 6

Sematonic stimergy is where…

Answer 6

The action of an agent is directly related to problem solving

Question 7

Sign-based stimergy is where…

Answer 7

The action of an agent affects the environment, but is not directly aimed at problem solving

Question 8

Ants have highly sophisticated [sematonic/sign-based] stimergy, where they communicate via […].

Answer 8

Sign-based, pheromones

Question 9

The stronger scented a pheromone trail is, the more likely an ant has been down this path before and [failed to return/returned safely], therefore it is [less/more] likely for an ant to take this path.

Answer 9

Returned safely, more

Question 10

In ACO, ants are […] that move along […] between nodes in a graph.

Answer 10

Agents, edges

Question 11

In ACO, an ant’s path represents a specific…

Answer 11

Candidate solution

Question 12

In ACO, after an ant has generated a candidate solution…

Answer 12

Pheromone is laid on that path

Question 13

In ACO, [more/less] pheromones are placed on a path based on the [ant/quality of the solution].

Answer 13

More, based on the quality of the solution

Question 14

In ACO, the initial graph begins with [no/equal/random] pheromone on along each edge.

Answer 14

Random

Question 15

In ACO, an ant does not return to a node it has already been to due to…

Answer 15

A tabulist describing the nodes it has already visited

Question 16

In ACO, after each [ant/iteration], we evaporate the pheromone.

Answer 16

Iteration

Question 17

In ACO, we define the probability that an ant will go to a city as…

Answer 17

The probability we are going to that city, divided by the probability we will go to the other cities

Question 18

In ACO, pheromones are updated using the update rule, which measures each update as…

Answer 18

The original pheromone multiplied by a learning rate coefficient, plus some measure of the quality of the path

Question 19

The Max-Min Ant System updates pheromone trails based on […] ants.

Answer 19

The best

Question 20

The Elitist Rank Ant System updates pheromone trails based on […] ants.

Answer 20

The best of a set number of

Question 21

Evolutionary algorithms like ACO can be applied to any problem as long as you have…

Answer 21

Relevant embedding

Question 22

A construction graph represents…

Answer 22

The construction of the problem, where we represent each decision horizontally as a node linked to each possible remaining choice

For example, given a graph of size 10, we start at the beginning node, then make some decision of the 9 remaining nodes. This becomes a new node, which is connected to 8 nodes, and so on.

Question 23

Swarm intelligence is defined as…

Answer 23

Emergent intelligent behaviour not possible by a single individual, but becomes possible as a group

Question 24

Collective movement is when…

Answer 24

A swarm moves as a collective in some way

Question 25

An example of collective, coordinated movement is... (pick one)

Answer 25

Flocking, swarming, formation travelling

Question 26

Movement is not considered collective if the movement is...

Answer 26

Movement that is pre-determined before the animal sets off or fixed movement, as it is not considered intelligent movement

Question 27

Flocking is a type of collective movement wherein the group exhibits...

Answer 27

Fast, directed movement with no leader that can react to predators and obstacles, while avoiding collision between flock members

Question 28

Flocking exhibits a balance between [...] and [...].

Answer 28

Attraction and repulsion

Question 29

Geese fly in a V-formation when migrating, in order to improve...

Answer 29

Aerodynamism

Question 30

Slime cast off by fish as they swim reduces turbulence in water, improving...

Answer 30

The consumption of energy of the fish behind them

Question 31

Flash expansion is a phenomenon observed in prey, wherein prey...

Answer 31

Dashes in all directions at once, in order to confuse the predator

Question 32

Boids are a type of algorithm that aims to simulate...

Answer 32

Flocking behaviours

Question 33

Each boid has a [...] that extends from the front of each boid.

Answer 33

Neighbourhood/vision cone

Question 34

The separation rule of boids states that a boid must...

Answer 34

Steer to avoid crowding local flockmates

Question 35

The alignment rule of boids states that a boid must...

Answer 35

Steer towards the average heading of the flockmates

Question 36

The cohesion rule of boids states that a boid must...

Answer 36

Steer towards the average position of the local flockmates

Question 37

If boids are started too close together, we may encounter...

Answer 37

Flash expansion

Question 38

If boids are started too far apart, we may encounter...

Answer 38

Slow aggregation, or small subflocks

Question 39

Particle Swarm Optimisation is an evolutionary algorithm inspired by flocking behaviour, used for the task of...

Answer 39

Finding the optimal set of continuous values for a task

Question 40

In PSO, each candidate solution is encoded as a...

Answer 40

Particle

Question 41

In PSO, the candidate space is a...

Answer 41

Swarm of particles

Question 42

In PSO, particles are physics objects that are only affected by [...] and [...].

Answer 42

Velocity and acceleration

Question 43

Particle Swarm Optimisation is a [competitive/collaborative] multi-agent system.

Answer 43

Collaborative

Question 44

In PSO, we begin by...

Answer 44

Initialising a number of random particles along the search space

Question 45

In PSO, for each timestep, we...

Answer 45

Update the velocity of each particle, then using that value to update position via addition

Question 46

In PSO, we update velocity by...

Answer 46

Taking the current velocity plus the distance to a random weighting of the particle's best encountered position and a random weighting of the distance to the population's best encountered position

Question 47

In PSO, besides max iterations and a lack of improvement, we terminate when...

Answer 47

The normalised swarm radius is close to zero, meaning the swarm has converged

Question 48

PSO can be updated to work on discrete spaces y...

Answer 48

Updating positions using the velocity as a probability threshold instead of an additive value

Question 49

An archive is a term used in multi-objective algorithms to describe...

Answer 49

The set of solutions described by a Pareto front approximation at a given timestep

Question 50

If a new solution dominates one of the solutions in a Pareto front archive...

Answer 50

We remove that solution and replace it with our new one

Question 51

If a new solution does not dominate one of the solutions in a Pareto front archive...

Answer 51

We mark it as dominated, then continue onto the next solution and evaluate again

Question 52

If a new solution does not dominate any of the solutions in a Pareto front archive...

Answer 52

We do not add it to the archive

Question 53

If a new solution does not dominate any of the solutions in a Pareto front archive, but is also not marked as dominated...

Answer 53

The archive is likely empty, hence we add it anyway

Question 54

It is difficult to find leaders in a large Pareto front archive because...

Answer 54

It is computationally expensive to do so

Question 55

Diversity preservation must be used in Pareto front archives to...

Answer 55

Preserve diversity in the set of solutions

Question 56

Clustering is a form of diversity preservation used in a Pareto front archive by...

Answer 56

Separating sets of solutions into clusters of solutions, keeping the solution with the minimum average distance to the cluster center

Question 57

Crowding distance is a form of diversity preservation used in a Pareto front archive by...

Answer 57

Scoring solutions according to their proximity to their neighbours, giving higher scores based on how far apart they are

Question 58

Leader selection must be used in Pareto front archives to...

Answer 58

Attract the swarm towards the set of non-dominated solutions on the Pareto front

Question 59

Random selection is used for leader selection in Pareto front archives by...

Answer 59

Selecting a random archive member, either truly randomly or using some weighted selection

Question 60

Dominated solution count is used for leader selection in Pareto front archives by...

Answer 60

Ranking the solutions in the archive based on the number of solutions they dominate

Question 61

Hypervolumes are used for leader selection in Pareto front archives by...

Answer 61

Picking the solution that has the largest hypervolume (the area it dominates between it and a given reference point)

Question 62

Many-objective PSO can be ranked using a ranking method like average rank, which...

Answer 62

Ranks the archived solution once for each objective, and takes the average of these ranks

Question 63

Many-objective PSO can be ranked using a ranking method like distance ranking, which...

Answer 63

Defines the rank of a solution based on the distance between each objective value