Lecture 11 - Swarm intelligence and Metaheuristics

Question 1

Swarm intelligence and metaheuristics

What is a machine?

Answer 1

entity capable of transfer and/or processing matter/energy

Question 2

Swarm intelligence and metaheuristics

What is an automaton?

Answer 2

entity capable of transfer and/or processing information

Question 3

Swarm intelligence and metaheuristics

What is a robot?

Answer 3

entity capable of transfer and/or processing both information and matter/energy

Question 4

Swarm intelligence and metaheuristics

What is intelligence?

Answer 4

analysis and/or synthesis of ordered patterns in an ‘unpredictable’ manner

Question 5

Swarm intelligence and metaheuristics

What does it mean to be unpredictable?

Answer 5

globally ‘intractable’ or ‘externally not-representable’

Question 6

Swarm intelligence and metaheuristics

What does it mean to be Intractable?

Answer 6

not computable in real-time

Question 7

Swarm intelligence and metaheuristics

What does it mean to be externally not-representable?

Answer 7

inaccessibility of internal states and representations

Question 8

Swarm intelligence and metaheuristics

What is the definition of an intelligent swarm?

Answer 8

“A group of non-intelligent robots forming, as a group, an intelligent robot. In other words, a group of ‘machines’ capable of forming ‘ordered’ material patterns ‘unpredictably’.”

Question 9

Swarm intelligence and metaheuristics

What are the key qualities of swarm intelligence in nature? (DNQSMS)

Answer 9

• Decentralized
• Not-synchronized
• Quasi-homogeneous
• Simple units
• Many (From hundreds to billions units, but not infinite)
• Stigmergy: modifying the environment for indirect communication

Question 10

Swarm intelligence and metaheuristics

What is flocking?

Answer 10

Movement of a swarm of agents with specific behavior.

Question 11

Swarm intelligence and metaheuristics

What are the 3 flocking rules of boids? (SAC)

Answer 11

• Separation: steer to avoid crowding local flockmates
• Alignment: steer towards the average heading of local flockmates
• Cohesion: steer to move towards the average position (center of mass) of local flockmates

Question 12

Swarm intelligence and metaheuristics

What are metaheuristics?

Answer 12

Search algorithms for solving complex optimization problems that are guided by a fitness function.

Question 13

Swarm intelligence and metaheuristics

Should metaheuristics find the optimal solution?

Answer 13

They’re mostly they’re concerned with A good solutions than THE best solution.

Question 14

Swarm intelligence and metaheuristics

What is the type of search a metaheuristic performs called?

Answer 14

It’s a partial search - finding a good solution, not necessarily the best one.

Question 15

Swarm intelligence and metaheuristics

Name the metaheuristics in this course (GAPS).

Answer 15

• Genetic algorithm (GA)
• Ant colony optimization (ACO)
• Particle swarm optimization (PSO)
• Simulated annealing (SA)

Question 16

Swarm intelligence and metaheuristics

Why is it called simulated annealing?

Answer 16

Name comes from cooling of metals - annealing.

Question 17

Swarm intelligence and metaheuristics

Describe the idea of simulated annealing (SA).

Answer 17

When running SA, new solution spaces are selected for exploration with a probability based on the temperature (parameter). The temperature decays as time goes by.

Question 18

Swarm intelligence and metaheuristics

Describe the idea of ant colony optimization (ACO).

Answer 18

ACO is an algorithm where agents explore the search space. They deposit pheromones to modify the environment (called stigmergy) as they explore, which probabilistically promotes other ants to explore that path.

Question 19

Swarm intelligence and metaheuristics

Describe the three components of particle swarm optimization (PSO).

Answer 19

• Momentum/inertia
• Own best position history
• Global best position

Question 20

Swarm intelligence and metaheuristics

How do you update a PSO particle’s position?

Answer 20

(Image)

Question 21

Swarm intelligence and metaheuristics

What is the ideal fitness function (mathematical definition)?

Answer 21

A convex function without local minima (Unless that local minima is a global minima).

Question 22

Swarm intelligence and metaheuristics

What is the easiest way to have a multi-objective fitness function?

Answer 22

Weight and sum each objective’s fitness.