# An Exploration of Mars Colonization with Agent-Based Modeling

Edgar Arguello 111Authors are listed in alphabetical order. Sam Carter
Cristina Grieg  Michael Hammer  Chris Prather  Clark Petri  Anamaria Berea222
Department of Computational Social Sciences, George Mason University

##  1 Introduction

Establishing a human settlement on Mars is an incredibly complex engineering
problem. The inhospitable nature of the Martian environment requires any
habitat to be largely self-sustaining. Beyond mining a few basic minerals and
water [4], the colonizers will be dependent on earth resupply and
replenishment of necessities via technological means, i.e., splitting martian
water into oxygen for breathing and hydrogen for fuel [6].

Our goal is to better understand the interactions of future Martian colonists
through an Agent-Based Modeling (ABM) approach. Accounting for engineering and
technological limitations, we draw on research regarding high performing teams
in isolated and high stress environments (ex: submarines, Arctic exploration,
war) to include psychological components within the ABM. Interactions between
agents with different psychological profiles are modeled at the individual
level while global events such as accidents or delays in earth resupply affect
the colony as a whole.

##  2 Space Settlements Literature Review

###  2.1 Use of Agent-Based Models to Simulate Small-Scale Communities

Given the many facets to the problem, a complex systems approach is
appropriate to extend our insights and avoid uninformed predictions later
[10]. ABMs may prove useful to help understand the ecological and demographic
conditions needed for sustainable resource-management in a constrained human
habitat [10]. It has been demonstrated that integrating Geographic Information
System (GIS) overlays and multi-agent simulation provides a means to explore
group behaviors which may be affected by an agent’s spatial knowledge of their
terrain [16]. ABMs provide useful “laboratories” for competing hypotheses to
identify rules of behavior that lead to group dynamics [16], which we would
then like to apply to our simulation of a potential Mars settlement.

###  2.2 Team and Interpersonal Psychology

The modern era of teams working in extreme conditions commenced with the
advent of nuclear submarines in the 1950s, the space race of the 1960s, and
expanded Arctic exploration of the 1900s [14]. These pursuits specifically
buoyed interest in how teams perform in extreme environments, what makes them
successful, and how individuals cope with the challenges presented by such
conditions. The technical sophistication necessary for persistent survival in
submarine missions or space exploration, coupled with their isolation and
inherent risks, position those endeavors as proxies for initializing a martian
colony ABM.

In a study of Antarctic exploration teams, researchers found that
psychological discomfort that occurred was limited to the individual or
between individuals levels and not the group as a whole [8]. Furthermore, the
researchers identified a steady linear increase in group tension over the
course of the mission. The interplay of individual interactions as well as a
broad and continual drain on psychological well-being, albeit minor, are
concepts which underpin much of our psychological modeling. It should be noted
that specific personality profiles as determined by psychological examination
were predictive of interpersonal cohesion in some instances [8], though these
considerations are an area for future research.

Attempts to connect quantitative biomarkers such as cortisol to psychological
examination performance while operating in extreme environments have shown
inconclusive results [18]. However, the same study did identify overarching
coping mechanisms of a submarine crew. While these mechanisms showed no
correlation to the personality profiles, they were beneficial. Traits such as
strong achievement motivation and interpersonal orientation were associated
with superior coping during submarine missions [18]. In another study of
submarine service, optimism, humor accompanied by cynicism, and a strong
perception of the submarine service were the primary coping mechanisms
exhibited by the crew [9]. Additionally, having some semblance of occasional
privacy with their own bed was a highly valuable coping mechanism, a
consideration for future research with more granular spatial modeling.

Research conducted on Soldiers and Marines during their deployment to Iraq
demonstrated that the intensity of combat situations is the primary
determinant of behavioral health challenges [2]. Other deployment-issues, such
as their length and frequency, also impacted the psychological health of the
studied Soldiers and Marines, albeit to a lesser extent than direct combat.

The present literature demonstrates that team and individual psychological
success in extreme environments can be broadly attributed to coping capacity,
which we define as the ability of people, organizations and systems, using
available skills and resources, to manage adverse conditions, risk or
disasters. Within the model, coping capacity is aggregated from a series of
sub-categories and quantitatively incorporated on a Cronbach alpha scale for
each individual agent. Cronbach’s alpha scoring is drawn from the
psychological changes in a 100-Day remote field groups study, where
researchers examined two Australian teams traversing across the Lambert
Glacier Basin, paying close attention to personality characteristics,
environmental factors, and interpersonal factors as predictors of Group
Tensions, Personal Morale, Emotional State, Cognitive Readiness, and the
Team’s Work-Life [8].

The agents within the model are categorized into four separate personality
categories: Agreeable, Social, Reactive, and Neurotic. Their coping ability
and resilience are linked to personality profiles typified by strong
instrumentality and achievement motivation combined with interpersonal
sensitivity. The four categories are drawn from the Positive Instrumental-
Expressive, the Hostile, Competitive Interpersonal orientation, and the low
achievement motivation combined with passive-aggressive characteristics linked
to Personality Characteristics Inventory (PCI) profiles which NASA has used
for screening, monitoring, and evaluating subjects in isolated and confined
extreme (ICE) environments [18]. The categorical measurements are as follows:

  * •

Agreeables - Individuals with the lowest degree of competitiveness, low
aggressiveness, and not fixated of stringent routine. Cronbach Alpha score
starting at 0.97

  * •

Socials - Individuals with a medium degree of competitiveness, extroverted,
require social interaction, but are not fixated on stringent routines.
Cronbach Alpha score starting at 0.94

  * •

Reactives - Individuals with a medium degree of competitiveness, competitive
interpersonal orientation, and fixated on stringent routines. Cronbach Alpha
score starting at 0.89

  * •

Neurotics - Individuals with a high degree of competitiveness, highly
aggressive interpersonal characteristics, and challenged ability to adapt to
boredom or a change in routine. Cronbach Alpha score starting at 0.84

Additionally, each agent is granted skills associated with their civilian and
military occupational specialties consistent with NASA’s Human Factors and
Behavioral Performance Element research, which analyzed the abilities that are
generalizable across circumstances and crew roles and those that will be
required by all crew members during a 30-month expedition to Mars [1].

The skills are broken up into two categories; Management (Skill 1) and
Engineer (Skill 2), which is extrapolated from NASA’s more comprehensive chart
of Leader, Pilot, Physician, Biologist, Geologist, Computer, Electrician,
Mechanic, and Combined [1]. The psychological structure of the model is
explored in more detail in section 3.

###  2.3 Martian Environment and Local Economy

Our challenge is to examine the unique institutional conditions required to
manage a settlement at such distance from Earth. In particular, we sought to
address the following questions: What conditions are needed to maintain a
stable colony on Mars? What combination of personality types would do best in
this hostile environment? How many resources are needed for two years between
resupplies and assuming occasional accidents? To tackle these questions, we
examined research relating to similar questions in four contexts: existing
ABMs, economic and related literature, ISS and Antarctica outpost data, and
agricultural research.

Collectively, the research suggests important design principles for Martian
economic modeling. Economic modeling of a remote settlement involves modeling
the external dependencies (food, etc.) and the internal labor and trade
economy of the settlement itself. Food is the single largest external
dependency. For example, food shipments arrive at the McMurtry and other
Antarctica settlements only once annually, so this provides us with a starting
point for calculating the estimated bi-annual shipments to Mars. Consequently,
the frequency and size of external food shipment, as well as the degree to
which a Mars settlement would attempt to grow food, are essential variables to
calibrate to model a sustainable Mars settlement.

Second, waste disposal and recycling (including carbon dioxide from humans and
other types of emissions from plants) are costs that must be included. Our
current focus is on supporting a stable population on Mars, so waste disposal,
recycling, economic gain from mining minerals, and other second order
considerations were left for future work.

Lastly, the degree of task differentiation in a settlement will directly
correlate to the extent that labor and food shipments generate an internal
bartering economy. Task differentiation is itself largely driven by the size
of the settlement, which is also critical to other parts of the economic
model. Developing a Martian economy is also left for future work.

###  2.4 External Martian Economy

To examine how a Martian economy might function outside of a colony, we looked
at other harsh environments with possible mineral deposits; the oceans and
Antarctica. Various countries have exploited mineral deposits in the oceans
before there were laws in place to govern mining or for the protection of
marine vegetation and wildlife. There is a call now to bring together the
fragmented efforts and explicitly address the protection of ocean
ecosystems.[12]

Exploration of Antarctica has gone differently given the lack of obvious
mineral deposits and the harsher environment. After the initial exploration
period during colonial times, there was a scientific period when all activity
on Antarctica was frozen and all signers of the Antarctic Treaty agreed to
collaborative, scientific exploration and experiments were allowed.[17] With
the possibility of mineral discovery, efforts are now underway to expand on
the original treaty to address additional uses.[3]

###  2.5 Energy Sources in Space

Energy sources are another key consideration for colonization. Solar power is
limited by daylight hours, seasonal variability, and dust accumulation on
solar panels.[11] We chose to model our colony on the nuclear power generator
employed by NASA and the U.S. Department of Energy for the Perseverance rover
in 2011. The Perseverance uses a Multi-Mission Radioisotope Thermoelectric
Generator (MMRTG) power system to provide a steady supply of electricity. The
MMRTG is expected to operate for at least 14 years, which is more than seven
times longer than the prime mission.[11]

Nuclear fission can be utilized to provide surface power on the moon and Mars,
and small, light fission reactors could provide up to 10 kilowatts of
electrical power for at least 10 years, according to a NASA website. This
would provide enough electricity to power several households. Together NASA
and DOE plan to design and test one of these low-enriched uranium systems on
the moon by the late 2020s.[5] For our Mars settlement we will assume a safe,
stable nuclear power generator.

###  2.6 Radiation

International space scientists have written on the threat particle radiation
poses to future human colonists of Mars. After four years on Mars, colonists
would be exposed to a level of radiation above what is assessed safe for
humans, according to the article.[19]Additionally the mission should depart
for Mars when solar activity is at its peak (the solar maximum), because the
increased solar activity deflects the most dangerous particles from distant
galaxies.

##  3 ABM description and ODD

###  3.1 KEY ASSUMPTIONS

Due to the complexity of the model, a variety of base assumptions were made:
1) Assume the Mars colony has already been constructed, that food, air and
water are being produced locally and will not require a start-up time to
create. 2) Assume a nuclear generator, similar to the Perseverance power
source, has been installed and the habitat has a steady electricity source for
at least 7 years.

###  3.2 PROBLEM FORMULATION

The main goal of the model is to simulate a theoretical habitat environment on
Mars for a colony carrying out the mining of minerals to be sent back to
Earth. There is an emphasis on the mental state of each Martian agent, since
that directly impacts the success of the mission.

###  3.3 MODEL DESCRIPTION

1\. Purpose

The agent-based model MARS-COLONY is intended to provide insights into the
possible scenarios that might develop from varying initial population sizes,
personality type and skill levels of colonists sent to run a mining colony for
minerals. The goal is to aid decision-makers with planning by highlighting
potential pit falls. To make the model as realistic as possible, research is
used on the studied coping capacities of common personality types, and random
accidents are introduced both transporting food from Earth, as well habitat
disasters on Mars that also lower food supplies. Accidents not only threaten
food supplies, but considerably increase stress levels of colony members.

The model was developed using NetLogo 6.2.

2\. Entities, State Variables, Scales There are two collectives and two agent
types in the model. The first agent type is the Martian, which represents a
single human member of the settlement. The entire group of Martian agents form
the collective “Martians”. The second agent type is the stressor, which can be
triggered by a settlement habitat accident or an earth shipping disaster. When
triggered, the stressor interacts with the Martians in the settlement to
reduce their coping capacity and health. A stressor can dissipate over time,
or can be removed by the Martian agents if they succeed a skills check to
recover from the habitat accident. Table 1 lists the attributes and starting
attribute values for Martian agents, and Table 2 lists the attribute and
starting values for stressor agents.

Attribute Name |  Description |  Starting Value (or Range)
---|---|---
coping-capacity |  psychological coping capacity of agents |  0.84 – 0.98
resilience |  coping category |  “neurotic”, “reactive”, “social”, or “agreeable”
skill-1 |  value of skill 1 |  0 - 100
skill-2 |  value of skill 2 |  0 - 100
health |  agent health value |  100
food |  food available for the given agent |  1
air |  air available for the given agent |  1
water |  water available for the given agent |  1
waste |  waste produced by the given agent |  1
partner |  the martian with which the agent is partnered, or ”nobody” if not partnered |  nobody
taskmate-food |  taskmate for food production |  nobody
taskmate-water |  taskmate for water production |  nobody
taskmate-air |  taskmate for air production |  nobody
taskmate-accident |  taskmate for habitat accident recovery |  nobody
taskmate-waste |  taskmate for waste removal |  nobody
Table 1: Agent Attributes: Martian Attribute Name |  Description |  Starting Value (or Range)
---|---|---
identity |  two types of stressor identity externalities |  “Shipping” or “Habitat”
Table 2: Entity Attributes: Stressor Figure 1: Martian Attributes

The settlement acts as additional entity, capable of storing air, food, water,
and waste, and having a set production capacity for these resources. Martian
agents interact with the settlement by working together to produce resources,
store resources, and consume settlement resources. The settlement is a 50x50
grid, with each grid cell having an individual resource production capacity,
but collective and unlimited storage. The geospatial location of each Martian
agent is randomly assigned during model initialization, and agents move
randomly around the grid. Table 3 lists the attributes and starting values for
the Martian settlement.

Attribute Name |  Description |  Starting Value (or Range)
---|---|---
p-food |  the rate at which food, on average, can be grown per time step in each patch of the settlement |  0.5
p-air |  air recycled per patch of the settlement |  5.88
p-water |  water recycled per patch of the settlement |  28
p-waste |  non-recyclable waste (i.e., fecal matter, plant emissions) processed per patch of the settlement |  0
settlement-air |  total air available for settlement |  5.88 * number-of-martians * 156
settlement-water |  total water available for settlement |  28 * number-of-martians * 156
settlement-food |  total food available for settlement |  10.5 * number-of-martians * 156
settlement-waste |  total waste produced by settlement |  0
settlement-minerals |  total minerals available for settlement |  0
Table 3: Entity Attributes: Settlement

The environment is the final entity, which determines the probability of a
habitat accident, earth shipment frequency and success probability, time
scale, technological efficiency, and production skill requirements. Table 4
lists the environmental attributes and starting values.

Attribute Name |  Description |  Starting Value (or Range)
---|---|---
ticks |  time step for model |  1 tick = 1 week
minerals-shipment |  amount of minerals received in each shipment from Earth |  100
food-shipment |  amount of food received in each shipment from Earth |  10.5 * number-of-martians * 78
shipment-frequency |  frequency of shipments from Earth |  78 ticks
technology |  technological efficiency |  0.5
energy |  energy (currently unused) |  1.0
food-s1 |  amount of skill 1 required to produce food |  0 - 100
food-s2 |  amount of skill 2 required to produce food |  0 - 100
water-s1 |  amount of skill 1 required to produce water |  0 - 100
water-s2 |  amount of skill 2 required to produce water |  0 - 100
air-s1 |  amount of skill 1 required to produce air |  0 - 100
air-s2 |  amount of skill 2 required to produce air |  0 - 100
waste-s1 |  amount of skill 1 required to produce waste |  0 - 100
waste-s2 |  amount of skill 2 required to produce waste |  0 - 100
accident-s1 |  amount of skill 1 required to recover from a habitat accident |  0 - 100
accident-s2 |  amount of skill 2 required to recover from a habitat accident |  0 - 100
Table 4: Entity Attributes: Environment

3\. Process overview and scheduling The only user input parameter currently in
the model is the initial number of Martians, which ranges from 4 – 152, in
increments of 4. When the model is initialized, the total number of Martians
are divided equally between four possible psychological categories: neurotic,
reactive, social, and agreeable. Martians, Stressors, the Settlement, and the
Environment are initialized with the values listed in Tables 1 – 4.

At each tick, Martians are able to move, sleep, team up with other Martians,
produce resources, consume resources, and engage socially. To move, the
Martians face a random direction and move forward one grid cell. Next, they
receive additional health from sleeping, with total health capped at 100.
Martians are then able to partner with other Martians to perform a skills
check for production. If the skills check is successful, they produce food,
water, and air, each with a unique skills check. Waste is produced as a by-
product of successful production. After resources are produced, they are then
consumed. Each Martian has a weekly requirement for food, water, and air. If
an individual Martian produces enough resources to meet this requirement, they
consume the defined amount and any remainder is contributed to the settlement
resource pool. If the Martian did not produce enough resources to meet the
weekly requirement, they consume the required resource amount from the
settlement resource pool. If the settlement resource pool does not have enough
resources to meet a Martian’s weekly requirement, the Martian’s health level
is reduced. Once the Martian’s health reaches zero, the Martian dies and is
removed from the model. Additionally, there is a small random chance of death
for each Martian to represent unforeseen mortality.

The settlement restores its production capacity for each grid cell and may
consume resources at each tick. Martian production is limited by the total
capacity of each settlement grid cell, and reduces the amount of producible
resources on that cell during the time step. At the next time step, the
resources are renewed to maintain a set weekly production capacity. The
settlement may also consume minerals, which are received from earth shipment,
to improve technological efficiency, which then improves Martian production
capability.

At each time step, the environment has a chance to add new Martians,
experience an earth shipping disaster, receive an earth shipment, and to
experience a habitat accident. Every 78 weeks, there is a chance that 4 new
Martians may be added to the colony from thr resupply shuttle, with a random
psychological category assigned upon addition. Also at 78 weeks, an earth
shipment may be received or there is a small random chance that an earth
shipping disaster may occur. If the earth shipment is received, the settlement
receives food and minerals, and improves technological efficiency. If an earth
shipping disaster occurs, the shipment is not received, and an earth shipping
disaster stressor is generated. There is also a small random chance of a
habitat accident occurring at each time step. If a habitat accident does
occur, it randomly affects either the food, water, air, or mineral settlement
resource supplies, and reduces the selected resource by half. It also
generates a habitat accident stressor.

If a stressor is generated, it has a chance to interact with Martians or to
dissipate over time. Habitat accident stressors persist until they dissipate
or are removed by a successful Martian skill check. While active, they
continue to reduce the settlement resource supplies. After 4 time steps, the
habitat accident stressor will dissipate and no longer affect the settlement
resource supplies.

4\. Design Concept

_Basic Principles_ The model was developed to explore the psychological,
social, technological, economic, and logistical factors that would influence
the long-term viability of a human Martian settlement. Martian settlers
interact with each other while producing and consuming resources, which
affects their overall health. They are divided into four personality types
that determine the degree and direction of this effect. Each Martian also
possesses a skillset that determines their success in producing resources for
themselves and the settlement. The settlement is supplied by regular shipments
from earth, which are susceptible to shipping disasters, and the settlement
can experience a habitat accident, both of which negatively influence
settlement supplies and overall Martian health.

_Emergence_ The primary observed emergent phenomenon occurs in the decline of
the Martian population. While the members of the settlement have an equal
probability of being affected by lack of settlement resources, habitat
accidents, or earth shipping disasters, Martians with the “neurotic”
psychology die at a much higher rate than those of other psychologies, and
once their population reaches a low enough level, the settlement population
stabilizes. Martians with the neurotic psychology and a high coping capacity
benefit the least from interaction with other Martians, and are penalized the
most if they have a low coping capacity. Our results suggest that this effect
is a driver of the Martian population decline, and once minimized or removed,
can produce a stable settlement.

_Adaptation_ The Martian agents do not have explicit adaptation, but do have
implicit adaptation in the use of their assigned skills. During each time
step, the model seeks to partner two Martian agents whose skills sum to the
required production threshold for resources or for habitat accident recovery
in the case of a habitat accident. This represents the idea that Martian
settlers would work together based on their actual skills to accomplish
various tasks needed to provide for the settlement, and would adapt as needed
for these tasks.

_Objectives_ The overall objective of the model is to produce a long-term
stable Martian population. Each Martian’s objective is to partner with other
Martians to produce resources and recover from habitat accidents. If Martians
are unable to produce sufficient resources, the population will begin to
decline, making future production more difficult due to a decline in the
available skills required for production.

_Sensing_ Martian agents move around the grid space and are able to sense
other agents within 3 grid spaces of themselves. If there are one or more
Martian agents within this range, a random agent is selected as a partner, and
the agents interact to increase or decrease overall health and coping
capacity, depending on current coping capacity and each agent’s psychological
category.

_Interaction_ In addition to interacting with agents in close spatial
proximity, as described in the section above, Martian agents also interact to
produce resources, recover from habitat accidents, and remove waste from the
settlement. Pairs of agents are selected by the model based on their skill
levels to achieve a set productivity threshold, which results in successful
achievement of these activities. If a pair cannot be made to reach the
threshold, the unpaired agents are not successful in production, recovery, or
waste removal. Stressor agents interact with the settlement to reduce resource
supplies or prevent an earth shipment from resupplying food and minerals.

_Stochasticity_ Stochasticity appears in the assignment of agent skill levels
and coping capacity, Martian agent movement, Martian death, Martian agent
addition, earth shipping disaster, habitat accidents, and Martian agent
teaming for production and interaction. When Martian agents are generated,
levels for their skills are assigned from a random uniform distribution for
the first skill, and the second skill then sums with the first to equal one
hundred. Martian agents move randomly around the grid space, and face a small
random probability of death at each time step. There are also random
probabilities of Martian agents being added to the model, the occurrence of an
earth shipping disaster when a shipment is due to arrive, or a habitat
accident occurring, with the type of resource affected by the habitat accident
also randomly selected. When agents pair up for resource production, habitat
accident recovery, or waste removal, the pairing is random given the pair
reaches the production threshold requirement. If agents are within three grid
cells of each other, they can randomly be assigned to interact to affect
health and coping capacity.

_Collectives_ Martian agents form a settlement collective, drawing on a pool
of shared resources and producing an overall amount of settlement waste. If an
individual agent is unable to produce enough resources for their own needs in
a given time step, they may draw on the collective settlement resources. If
they produce excess resources, they are contributed to the settlement resource
pool.

_Observation_ Outputs collected from the model for observation include coping
capacity statistics, number of Martian agents, total settlement resources,
shipments received, shipping disasters and habitat accidents experienced,
population coping and resilience, overall Martian health, and time elapsed.

5\. Initialization

The setup procedure imports a Martian landscape of geographic files. The
global variables are then checked for total water, food and air for the
habitat. Also total energy and technology levels needed to run the habitat and
mine minerals. Additional parameters are assigned for the frequency of
shipment and habitat accidents. Every 78 ticks there is also a slight chance
of a birth or death in the community. The individual Martian attributes are
then calculated by dividing resources equally, and randomly assigning
personality types and skill.

6\. Input Data Geographic Information System (GIS) files of the Mars landscape
have been loaded for awareness, but no input data is used in this model. Mars
exploration is still in the early stages and applicable data is not yet
available.

###  3.4 SETTING PARAMETERS

One of the challenges of agent-based modeling is determining how to set the
initial parameters for the model. Empirical data are often a source of initial
parameters, even in far-flung scenarios such as past civilizations or extra-
planetary settlements. Our model draws upon a number of sources to set our
parameters.

Global Variables. The Earth shipment and shipment frequency variables are
discussed above. This discussion also excludes shipping and accident counter
variables, which are discussed under results. The other global variables
include the settlement’s total resource stockpiles (settlement-air,
settlement-food, and settlement-water). The values of the parameters are
primarily derived from a review of the resource storage and production
capabilities of the International Space Station (ISS). NASA states that a
single ISS resident consumes 5.88kg of air, 28L of water, and 10.5kg of food
in a given week.[7][13][15] Our initial settlement-food, settlement-air, and
settlement-water assume a ramp-up, pre-settlement series of deliveries that
stockpile supplies equal to two earth shipment cycles (156 weeks/time steps).

However, there are proven technologies from the ISS to allow for the
sustainable production of air and water. Conversely, there is as yet no method
for the sustainable production of food in low gravity. As a result, we assume
that earth shipments will deliver food but not water or air. Earth shipments
deliver sufficient food for one additional earth shipment cycle (10.5kg of
food per settler per week).

Our global variables also define several other rates necessary to the function
of the settlement. The technology parameter sets a rate of aggregate
technological efficiency. This term serves as a modifier to the amount of
production generated by labor in the settlement. Technology is initially set
at 0.5

For this early version of the model, energy serves as a similar term that
specifies the amount of resource consumption required for the settlement to
function. This placeholder value is set at 1.0.

Lastly, the global variables set the skill levels necessary for settlement
production functions. An assumed score of 100 is needed across two sets of
skills (-s1 and -s2) to successfully accomplish each of four tasks (food,
water, air production, and accident recovery). Each pair of scores related to
resource production is set with the same values. For example, food-s1 is set
as a random integer between 0 and 100. Food-s2 is set as the difference
between 100 and food-s1 (100 - food-s1). Accident recovery sets both both
accident-s1 and accident-s2 as a random integer from 0 to 100. This represents
the ex ante uncertainty about what types of skills may be needed for a given
emergency. It is important to remember that these values set the required
skill score that must be met for successful production; they do not guarantee
that settlers will have these skills.

Settler Variables. Settlers are assigned two skills. Skill 1 is set as a
random number from 0 to 100. Skill 2 is set as 100 - Skill 1, such that each
settler has a total skill level of 100. Settlers have a partner variable (all
settlers begin unpartnered) and indicator variables that store their task
assignment.

Each settler is created with one of four resilience types: nuerotic, reactive,
social, and agreeable. Each of these resilience types are assigned a coping
score based on our research in team function and group theory. These coping
scores are 0.84, 0.89, 0.94, and 0.98. Coping scores determine how settlers
continue to produce and consume resources after adverse events such as a
habitat accident.

Settlement (Patch) Variables. Patch variables in this model represent the
modest estimated amount of food production that could be generated in a garden
or farm (0.5 kg per patch per time step), the WRPS + WTS air production system
(5.88kg per patch per time step), and OPS water recycling capacity (28L per
patch per time step). These production levels are activated in the production
functions only with the requisite levels of settler skill levels, as discussed
above.

Exogenous Variables. This model contains only two exogenous variables: the
starting number of settlers and the number of time steps in a given model run.

###  3.5 IMPLEMENTATION VERIFICATION

Our code shows cyclical variability in the population sizes and is able to
stabilize. The code appears to run correctly, the colonists have plenty of
resources, and we are able to focus on the interaction between the different
personality types. However we are unable to validate the values since there
has not been an actual Mars colony we can compare data to so model data serves
largely to highlight problems for consideration.

##  4 Scenarios for a Stable Mars Settlement

###  4.1 A Stable Population Size

Our goal was to see which initial population sizes lead to a stable colony
size. We did 5 runs of our model, for 28 Earth years, varying the initial
population size from 10 to 170 by steps of 10. Given that there are 4 critical
tasks that are needed continuously (air, water, food production and waste
removal) in addition to handling disasters, and two skills needed for each
task, we chose a population size of 10 as the minimum needed for a ”stable”
colony size. The population is allowed to dip below 10 as long as it bounces
back within 1.5 years, or the amount of time between Earth resupply shuttles.
A plot of our runs below shows that all initial population sizes above 50 were
able to maintain a population above 10 for all time steps. We will therefore
only consider initial populations below 50 as we try to determine a minimum
initial population which is able to maintain, or bounce back quickly to, a
stable colony size equal to or greater than 10 for all 28 years.

Figure 2: Variation in number of agents at each time Step (one week) in the
simulation.

Since our 4 personality types are equally distributed at setup, for our focus
on smaller initial populations we started at 10 (the minimum for a stable
colony), then increased to 50 with a step size of 4. Each time tick in our
model represents a week, so 1.5 years is equivalent to 84 ticks.

For an initial population of 10, the plot below shows the population sizes
over 28 years with prolonged time periods when the population drops below 10

Figure 3: Population sustainability with a start of population = 10.

For an initial population size of 22, the plot below show the population sizes
over 28 years remains above 10, meeting our definition of a stable colony.

Figure 4: Population sustainability with a start of population = 22.

A summary of which small initial population sizes resulted in stable colonies
over 28 years, in 5 runs, is given in the table below. For the purpose of this
model, an initial population of 22 was the minimum required to maintain a
viable colony size over the long run.

Initial Population Size |  Does Population Size Bounce Back Above 10 or Not
---|---
10 |  No Bounce Back
14 |  No Bounce Back
18 |  No Bounce Back
22 |  Successful Bounce Back
26 |  No Bounce Back
30 |  Successful Bounce Back
34 |  Successful Bounce Back
38 |  No Bounce Back
42 |  Successful Bounce Back
46 |  Successful Bounce Back
50 |  Successful Bounce Back
Table 5: Small Initial Populations Which Do and Do Not Lead to Stable Colonies

###  4.2 An Agreeable Personality Type Does Best

In all runs, the Agreeable personality type was the only one to survive the
full duration of model runs. This is likely because it has the highest coping
capability, and after long periods of time every agent has been exposed to a
series of stressor interactions, as well as space and habitat accidents. The
picture of the MARS-COLONY NetLogo model below includes a visualization of
total personality types over time, and the yellow Agreeable personality type
is most resilient, the Neurotic personality type was the most likely to fail,
the Reactive and Social personality types alternated in between. While this
model assigns equal numbers of each personality type, future work could try
adjusting the proportion of each to possibly lead to a lower required minimum
initial population. For example, a crew of all Agreeable personalities may be
more successful.

Figure 5: Screenshot of the simulation in NetLogo.

###  4.3 Maintaining Sufficient Resources Despite Accidents

Our data analysis shows that our food supplies are more than sufficiently
resupplied with earth shipments, for the majority of time steps, even in
scenarios where there are shipping disasters. Since the focus of this study
was to examine the interplay of the 4 personality types we did not assume any
production of air, water or food on the colony. Instead we provided multiple
years of initial supplies, with resupplies on incoming shuttles. Similarly we
were not concerned with the amount of waste generated by the colonists. Future
work can focus on this area of the model and explore the trade off between
resources needed from Earth, and amounts that could be generated on Mars. This
is a vital component to establishing a stable colony which adds to the
complexity of the model.

##  5 Conclusion

In summary, the MARS-COLONY Agent-Based Model offers a preliminary look at
necessary conditions to establish a stable mining colony on Mars. The main
focus is on the personality types of colonists selected and how they perform
throughout their time on Mars, using their skills to mine minerals and react
to random resupply shuttle accidents or habitat disasters. The stress caused
by accidents, as well as from interacting with other colonists, takes a toll
and Agreeable personality types were assessed to be the most enduring for the
long term, whereas Neurotics showed least adaptation capacity. This study
assumed a steady available nuclear energy supply and sufficient initial air,
water and food with sufficient resupply in order to focus on personality and
mental health of colonists, however those are recommended areas of future
work.

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