What distinguishes genotype from phenotype?

Genotype = DNA, phenotype = physical traits

What is the definition of Evaluation in Genetic Algorithm Process?

Convert genotypes -> phenotypes, evaluate fitness

What is the definition of Mutation in Genetic Algorithm Process?

Randomly flip bits in offspring to add variation

What is the main purpose of the Evolution Theory Crash Course in relation to Genetic Algorithms?

To introduce biological evolution concepts that inspire GA in computing

What does the "crossover" step do in genetic algorithms

Mix two parent solutions to make a new one

The role of evolving morphology

Allows AI to design its own physical form

Describe the term for variation

Difference among individuals in a population

Select true statement:

Norbert Wiener - Father of cybernetics, John Holland - Credited with formalizing genetic algorithm

What was Frank Rosenblatt's contribution in late 1960s?

He invented the perceptron, an early model of a neural network.

Computational Parallelism can improve which part of the threads?

Improves computational and execution speed.

What did John Holland achieved?

Credited with formalizing genetic algorithms

What distinguishes connectionism from cybernetics in early bio-AI systems?

Cybernetics used control theory; connectionism used networks

What does the schema theorem explain in GA operation?

Survival of fit patterns in genotypes

What is the purpose of bio-inspired computing?

Natural processes for computational tasks like optimization and learning

What is the definition of Initialization in Genetic Algorithm Process?

Randomly generate initial population of solutions

What terms described the meaning of Phenotype?

Expressed traits depend on which living organism were tested.

What is the main goal of a genetic algorithm

to find the best or nearly best solution in a large search space

How does roulette wheel selection ensure diversity in a GA population?

Fitness-weighted chance allows weak survival

Biological processes such as:

Neural Activity, Evolution, Genetices, Self-regulation

What is the definition of Repeat in Genetic Algorithm Process?

Continue through multiple generations until a stopping condition is met

Which era introduced cybernetics as a control system theory in bio-inspired computing?

1950s, focused on control in machines and animals

What is the difference between genotype and phenotype?

Genotype is DNA; phenotype is observable traits result of DNA & env

What does a "Genotype" represent in morphology?

A directed graph of body parts and connections

According to the 2019 Swarm and Evolutionary Computation journal review, what has bio-inspired computing emerged as?

One of the most studied branches of AI

How does roulette wheel selection contribute to genetic diversity?

It gives weaker individuals a chance to reproduce

What happens during the final step of the Genetic Algorithm process?

Continue through multiple generations until a stop condition is met

What is an example of computational parallelism in genetic algorithms?

Evaluating the fitness of multiple individuals simultaneously

According to schema theory, what is a schema in genetic algorithms?

A pattern in a genotype (e.g., 1**0*)

Which following answer is correct regarding the breakthrough of DeepMind's AI system AlphaFold?

AI Model capable of predicting 3D protein structure from DNA.

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Answers

1
What distinguishes genotype from phenotype?
Genotype is visible traits, phenotype is inherited
Genotype is behavior, phenotype is DNA
Genotype changes over time, phenotype is fixed
Genotype = DNA, phenotype = physical traits
2
What is the definition of Evaluation in Genetic Algorithm Process?
Randomly generate initial population of solutions
Convert genotypes -> phenotypes, evaluate fitness
Combine parts of two parents to create offspring
Choose individuals for breeding
3
What is the definition of Mutation in Genetic Algorithm Process?
Randomly flip bits in offspring to add variation
Continue through multiple generations until a stopping condition is met
Randomly generate initial population of solutions
Convert genotypes -> phenotypes, evaluate fitness
4
What is the main purpose of the Evolution Theory Crash Course in relation to Genetic Algorithms?
To analyze protein structures for medical research
To explain how to build DNA models in a lab
To introduce biological evolution concepts that inspire GA in computing
To teach the anatomy of living organisms
5
In the airplane wing example, what does the fitness test measure ?
how long the wing is
the color of the wing
the shape of the wing
how much lift the wing creates
6
In the airplane wing design example, how many possible wing designs exist with a 9-bit genotype?
128
1024
512
256
7
What does the "crossover" step do in genetic algorithms
Add random changes
Choose the strongest solution
Change the fitness score
Mix two parent solutions to make a new one
8
The role of evolving morphology
Evolved network that enables locomotion
Allows AI to design its own physical form
Enables recursive, modular body generation
Set the foundation for modern morphological AI and evolutionary robotics
9
What are the inputs of control system: Neural-like Network?
Motor command to actuators
Emerges from interaction between control system and morphology
Sensors
A directed graph
10
Which are components of the genotype â†’ phenotype â†’ fitness cycle in GA?
C â†’ B â†’ A
B â†’ C â†’ A
A â†’ B â†’ C
C â†’ A â†’ B
11
How many dimensional spaces complexity that often happned in real-world?
Depend on the situation.
10000000
1 billion
100+
12
Describe the term for variation
Encoded genetic information
Success of a phenotype in a given environment
The ability to pass traits to offspring
Difference among individuals in a population
13
Choose the suitable genetic algorithm for genotype
Fitness evaluation
Iterative improve of solutions
Encoded solution
Real world behaviour
14
Select true statement:
Frank Rosenblatt - Focus on coordination systems
Norbert Wiener - Father of cybernetics
Chris Langton - Inventor of Perceptron
John Holland - Credited with formalizing genetic algorithm
15
Randomly flipping bits in offspring to introduce variation is called __________.
mutation
reproduction
crossover
encoding
16
How does the organism functions and interacts with its environment?
Phenotype
DNA
Genotype
3D structure of proteins
17
What was Frank Rosenblatt's contribution in late 1960s?
He designed the first computer to defeat a human in chess.
He invented the perceptron, an early model of a neural network.
Developed backpropagation algorithm used in training dnn
He introduced convolutional neural networks for image processing.
18
Computational Parallelism can improve which part of the threads?
Reducing data transfer between storage devices.
Increasing an amount of data stored in memory.
Improves computational and execution speed.
Correctly predict and coordinate the timing of thread execution.
19
What are causes of differences between offspring and their parents in GA?
Selection Pressure
All
Crossover
Mutation
20
What did John Holland achieved?
Credited with formalizing genetic algorithms
Pioneer of artificial life movement
Father of cybernetics
Inventor of the perceptron
21
What distinguishes connectionism from cybernetics in early bio-AI systems?
Both used symbolic logic exclusively
Cybernetics used control theory; connectionism used networks
Cybernetics lacked any feedback models
Connectionism avoided biological analogies
22
What type of graph supports recursive, modular body design?
Flowchart
Directed graph
Pie chart
Circular graph
23
What does the schema theorem explain in GA operation?
Why populations shrink over time
Survival of fit patterns in genotypes
Fast mutation of selection function
How optimal solutions are encoded
24
What is the purpose of bio-inspired computing?
To simulate emotions in AI
Natural processes for computational tasks like optimization and learning
To enhance cybersecurity systems through brute-force learning
To model algorithms using social behavior
25
Choose the correct sequence of steps in a genetic algorithm.
vi, i, ii, v, iii, iv
vi, ii, i, iii, iv, v
iii, v, iv, i, vi, ii
v, i, iii, iv, ii, vi
26
Who coined the term "cybernetics"?
Frank Rosenblatt
Chris Langton
John Holland
Nobert Wiener
27
What is the definition of Initialization in Genetic Algorithm Process?
Continue through multiple generations until a stopping condition is met
Convert genotypes -> phenotypes, evaluate fitness
Randomly generate initial population of solutions
Randomly flip bits in offspring to add variation
28
What does 'fitness' mean in genetic algorithm
How long you live
How much DNA you have
How well you do in a test
how fast you can change
29
What terms described the meaning of Phenotype?
Environmental test determining fitness.
The ability to pass traits to offspring.
Expressed traits depend on which living organism were tested.
Differences among individuals in a population.
30
What is the main goal of a genetic algorithm
To draw pictures
To delete random data
to find the best or nearly best solution in a large search space
to copy human DNA
31
How does roulette wheel selection ensure diversity in a GA population?
Only the best are selected repeatedly
Random bit flip occurs in crossover
All individuals have equal chance
Fitness-weighted chance allows weak survival
32
The genetic algorithm continues evolving the population until a __________ is met.
perfect genotype
random mutation
fixed phenotype
stopping condition
33
Which of the following is NOT one of the three main stages of the evolutionary cycle?
Selection & Breeding
Variation & Heredity
Mutation Analysis
Testing
34
The year Connection Machine CM-5 is created in?
1994
1984
2004
1965
35
Who is Father of cybernetics?
Norbert Wiener
Chirs Langton
John Holland
W.Ross Ashby
36
Biological processes such as:
Neural Activity
Evolution
Genetices
Self-regulation
37
What is the definition of Repeat in Genetic Algorithm Process?
Combine parts of two parents to create offspring
Convert genotypes -> phenotypes, evaluate fitness
Continue through multiple generations until a stopping condition is met
Randomly flip bits in offspring to add variation
38
Which era introduced cybernetics as a control system theory in bio-inspired computing?
1980s, focused on evolutionary robotics
1970s, focused on deep neural networks
1960s, focused on robot vision
1950s, focused on control in machines and animals
39
Which of the following is not a fitness function used in the simulation?
Walking distance
Light-seeking
Jumping height
Swimming efficiency
40
Phenotype (3D creatures) graph is expressed by
body form
pyhsical form
phscyological form
graphical form
41
What is the difference between genotype and phenotype?
Genotype is DNA; phenotype is observable traits result of DNA & env
Genotype is observable traits; phenotype is environmental data
Genotype is behavior; phenotype is genetic code
Genotype changes frequently; phenotype is constant
42
What does a "Genotype" represent in morphology?
A score of how well the creature walks
A directed graph of body parts and connections
The sensor input system
The creatureâ€™s personality
43
According to the 2019 Swarm and Evolutionary Computation journal review, what has bio-inspired computing emerged as?
A tool for building mobile apps
One of the most studied branches of AI
A minor concept in genetic research
A fading trend in AI history
44
How does roulette wheel selection contribute to genetic diversity?
It gives weaker individuals a chance to reproduce
It eliminates weak individuals early
It selects only the best-performing individuals
It randomly selects individuals without fitness consideration
45
What happens during the final step of the Genetic Algorithm process?
Continue through multiple generations until a stop condition is met
Randomly generate initial population of solutions
Choose individuals for breeding
Randomly flip bits in offspring to add variation
46
What is an example of computational parallelism in genetic algorithms?
Evaluating the fitness of multiple individuals simultaneously
Running the GA on paper
Performing crossover and mutation in isolation
Freezing the genotype of one parent
47
In Roulete Wheel Selection, Each individual is given a slice of virtual wheel ______________________
Proportional to Fitness.
Based on the genertic diversity among the communities.
Follow its mutation rate.
randomly assigned regardless to fitness.
48
What is an example of selection pressure
A math test in school
Climbing a hill to get food
A game of chess
Reading a book quietly
49
According to schema theory, what is a schema in genetic algorithms?
A hardware-accelerated algorithm
A pattern in a genotype (e.g., 1**0*)
A high-level overview of population fitness
A specific solution that is optimal
50
Which following answer is correct regarding the breakthrough of DeepMind's AI system AlphaFold?
Ability to pass traits to offsprings.
Encoded genetic information
AI Model capable of predicting 3D protein structure from DNA.
Key Milestone in bio-AI convergence.
51
Choose the right word quited by Chris Langton and Nils Aall Barricelli on the core idea of artificial life.
"No one can stop progress of artificial intellligence"
"Life as it could be."
"Pride makes us artificial and humility makes us real"
"Every problem is solved by yet another indirection."
52
According to Goldberg & Holland, a Genetic Algorithm is best described as:
A rule-based system for logic inference
A manual search process for model tuning
A probabilistic search procedure for large spaces using strings
A deterministic algorithm for small datasets
53
What roles do proteins play in the expression of genetic information? Select all that apply:
Proteins are only used in muscle and tissue, not in behavior.
Proteins are formed directly from DNA without any intermediaries.
Proteins fold into 3D structures that determine traits and behavior.
Proteins are built from amino acids translated from DNA codons.
54
Richard Dawkins "Biomorphs" demonstrate the ___________________ via simples rules and based on user selection.
Evolution of Complexity
Control System
Fitness Function
Morphology Representation
55
What is the 3 main stages of evolutionary cycle?
Testing (Selection Pressure)
Selection & Breeding
DNA
Variation & Heredity
56
What are the steps in the genetic algorithm process?
Eval â†’ Crossover â†’ Select â†’ Init â†’ Mutation
Init â†’ Crossover â†’ Select â†’ Eval â†’ Mutation
Init â†’ Crossover â†’ Repeat â†’ Eval â†’ Mutation
Init â†’ Eval â†’ Select â†’ Crossover â†’ Mutation
57
What are the component of the Neural-like Network control system?
Behaviour
Outputs
Inputs
Network
58
What is the definition of Crossover in Genetic Algorithm Process?
Convert genotypes -> phenotypes, evaluate fitness
Randomly generate initial population of solutions
Continue through multiple generations until a stopping condition is met
Combine parts of two parents to create offspring
59
Which of the following is NOT listed as a biological process that inspires bio-inspired computing?
Self-regulation
Natural selection
Evolution
Neural activity
60
Which is considered as a major subfield of AI?
Robotics
Bio-inspired computing
Machine Learning
Optimization
61
Who is credited with inventing the Perceptron, laying the foundation for modern deep learning?
Frank Rosenblatt
John Holland
Norbert Wiener
Chris Langton
62
Choose the correct answer that is True about 3 main stages of Evolutionary cycles.
New individuals help assess fitness in a population.
Selection & breeding combine best parents to produce offspring.
Testing randomly alters individuals to add diversity.
Different head and leg sizes show variation and heredity.
63
Which field is associated with simulating life-like systems such as self-replicating organisms?
Cybernetics
Artificial Life (A-Life)
Genetic Algorithms
Robotics
64
What it means by computional parallelism?
Implementation level parallelism in hardware and software
Evaluating fitness of multiple individuals in a generation
GAs evaluation can be parallelized on multiple processors or threads
Improve computional speed
65
What was the name of Karl Sims' 1994 paper?
Evolving Virtual Creatures
Robotic AI Forms
Morph AI Simulation
The Evolution Machine
66
What is the definition of Selection in Genetic Algorithm Process?
Randomly flip bits in offspring to add variation
Choose individuals for breeding
Randomly generate initial population of solutions
Combine parts of two parents to create offspring
67
Which schema is true pattern in a genotype in Schema Theorem?
**0
1**0*
01**0*
All of the above
68
What does implicit parallelism mean?
GAs evaluation can be parallelized
GAs maintain and evolve multiple selections in parallel
Keep genetic diversity
Give weaker solutions a chance too
69
How did Karl Sims represent morphology in his 3D virtual creatures?
With binary genome encoding only
As recursive directed graphs
As layers of neurons
Using symbolic math expressions
70
What does it mean for having implicit parallelism?
Keep genetics diversity and allow multiple "bloodline" to co-exist.
they can be parallelized on multiple processors or threads.
maintaining and evolve multiple solutions at once.
Use the roulette wheel selection process.
71
What does "Phenotype" represent in evolving morphology?
A random mutation
The graph of ideas
The actual 3D physical creature
A fitness score
72
What is the meaning for fitness?
Encoded string representation
Evaluation of the phenotype
Decoded solution
Find optimal or near optimal solution
73
What is "Evolving Morphology"?
Changing colors of animals
Manually building robot shapes
Using genetic algorithms to evolve physical forms
Using AI to draw images
74
Why did Karl Sims use fitness metrics like distance in his simulations?
To evaluate morphology complexity
To tune neural weights directly
To guide evolution via performance
To limit mutation rates in genotypes
75
In evolution theory, why is phenotype not always identical to genotype?
Genotype cannot change at all
Genotype controls only external traits
Phenotype is affected by environment
Phenotype is randomly mutated only
76
Which best explains 'implicit parallelism' in GA evolution?
Splitting selection into threads
Testing multiple genotypes at once
Coding loops in GA algorithms
GPU-based crossover and mutation
77
In the evolutionary cycle, what happens during the Testing (Selection Pressure) stage?
DNA mutations are introduced.
Organisms are randomly selected for reproduction.
Offspring are produced by asexual reproduction.
Individuals are evaluated based on performance in a fitness challenge.
78
How does the population adapt to the environment?
Evolves
Inheritable
Mutation
Crossover
79
Genotype is represent by using?
Nodes
Body parts
Connection between parts
Edges
80
According to the notes, what does DeepMind's AlphaFold AI model predict
DNA mutations over generations
Behavior patterns based on environment
Breeding success in artificial organisms
Protein folding structures from DNA sequences
81
The mutation often prevent premature convengergence and maintains _________________
Overfitting in training model
Genetic Diversity
rapid convergence to local optima and propotional to fitness.
homogeneity among solution
82
A genetic algorithm is a __________ search algorithm inspired by natural evolution.
probabilistic
heuristic
deterministic
recursive
83
Why repeated evolution was interative in improving population over the time?
Each generation's mutations help enhance fitness.
It explores more solutions and gets closer to optimal options.
All of the above
GAs rely on improvement via selection, crossover, and mutation.
84
What is a key limitation of simple search algorithms like hill-climbing?
They require large amounts of memory
They get stuck in local maxima
They always converge to global optima
They do not work with binary data
85
In 1994, __ is developed on being the fastest supercomputer at the time
IBM
Agent57
DeepFive
Connection Machine CM-5
86
Hyperplane Sampling often involving:
i, ii
i, iv
ii, iv
iii, iv
87
What are the specification of Search Space Complexity?
Full of local maxima
Irregular
Non-linear
All
88
According to the Swarm and Evolutionary Computation journal review, what year was bio-inspired computing part of AI?
2020
2013
2019
2015
89
Choose correct bio sequence from DNA to phenotype use as inspiration in GA?
A â†’ B â†’ C â†’ D
B â†’ C â†’ D â†’ A
C â†’ A â†’ B â†’ D
C â†’ B â†’ A â†’ D
90
Which of the following are not definitions of bio-inspired computing?
Method using biological hardware for computing
Algorithms inspired by organisms like ants & bacteria
Interdisciplinary field combining biology and AI
Computational designs using natural metaphors
91
Which following are connected to the application to Genetic Algorithm?
Data encryption using quantum mechanics.
Fitness evaluation and real-world behaviour modeling.
Traditional sequencial programming that process without equation.
Statics rules based expert system with observable traits.
92
Why is mutation essential in genetic algorithms even with good crossover?
It eliminates all low-fitness solutions
It optimizes only the best solution
It compresses the genome size
It adds new genetic material to population
93
What does the fitness function do in a genetic algorithm?
Selects the mutation rate
Defines the genome size
Encodes the phenotype
Measures how well a solution performs
94
What is the correct order of the three main stages in evolutionary cycle
Breeding -> Fitness -> Variation
Variation & Heredity -> Testing -> Selection & Breeding
testing -> selecting & breeding -> variation
Heredity -> Mutation -> Fitness
95
Which aspect directly supports heredity in evolutionary computation models?
Crossover of phenotypes
Mutation of environments
Evaluation via phenotype ranking
Inheritance of genotypes
96
The purpose of hyperplane sampling
Understand the problem of limited search in simple algorithm
Allow combining partial solutions across different genotypes
Explain how useful genetic structures
Multiple evolving subpopulations maintain diversity
97
What is the definition for search space complexity?
Amount of memory space an algorithm uses to store the search space itself
Search across the entire space
GAs preserve and recombine good schemas across dimensional
Real world problems often exist in high dimensional spaces
98
Why is implicit parallelism important in genetic algorithms? Select all that apply.
It ensures diversity in the population
It makes the algorithm deterministic
It allows hardware-level parallel computing
It enables multiple schemas to evolve at once
99
What was the purposes of the studies Evolving Virtual Creatures (1994)?
How morphology, control, fitness & mutation work in computation.
Using machine learning to create 3D virtual environments.
Creating interaction between morphology and control systems.
Showing how fit patterns evolve to be preserved and amplified.
100
What task of fitness function that demonstrated the proximity to a light source for simulation?
Competition
Swimming
Walking
Light-seeking

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