character development & adaptive decision making in games · computer interactions (poznanski...

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Character Development & Adaptive

Decision Making in Games

Abertay University

By Jack Armour

2016

Jack Armour | 1100891 Character Development & Decision Making in Games

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ABSTRACT

Games today are more visually realistic than ever, but their AI and characters are still

basically unchanged from the earliest games. This project aims to create a simple yet

effective way to bring any non-player character to life, using personality and character

development, thus making games more enjoyable for players. The application built

tested how the Five Factor Model of Personality can be used to create a realistic AI,

and how developing and changing the personality would effect its realism. The

program took 'situation', 'personality', 'mood', and 'emotion' as inputs and output a

decision to deal with the situation. The results of this paper found that using

personality, specifically the Five Factor Model of Personality, seems to be a great way

to represent personality in games, as it produced meaningful and realistic choices. It

was found however that situations that are more abstract like 'explore' must be more

detailed, as sometimes the AI would choose inappropriate actions, and leave the

situation unsolved. Results also shows that people who tested the character

development found them much more realistic than those who just tested the decision

making without personality development. However, more work needs to be done on

how the personality develops in this type of agent, as problems were discovered with

the method used in this project.

In conclusion, the Five Factor Model of Personality is a great way to represent

personality in believable agents, games, and other applications. The development of

these personalities is definitely a step in the right direction for truly realistic personal

human computer interactions with AI.


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FOREWORD

First of all, I would like to thank God for all his amazing grace that has carried me

through to finish this dissertation. I would also like to thank my mentor, David King

for his help and guidance writing this dissertation and throughout the project, my

girlfriend, Yoan for motivating me and helping me with editing and proof reading.

Also my friends and families for their never ending love and support.


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TABLE OF CONTENTS

Abstract...........................................................................................................................ii

Foreword.......................................................................................................................iii

List of Figure.................................................................................................................vi

List of Tables................................................................................................................vii

1. Introduction.................................................................................................................1

1.1 Setting the Scene...........................................................................................1

1.2 Background...................................................................................................1

1.3 Aims..............................................................................................................3

1.4 Research Questions......................................................................................3

2. Literature Review.......................................................................................................5

2.1. Modern Video Games..................................................................................5

2.1.1. The Interactive Media...................................................................5

2.1.2. The Characters and Possible Techniques to Create Them........... 5

2.2. Real People..................................................................................................7

2.2.1. Personality....................................................................................7

2.2.2. Choice...........................................................................................9

2.3. Creation of Personality..............................................................................11

2.3.1. Uses............................................................................................11

2.3.2. Research......................................................................................11

2.3.3. The Future...................................................................................12

3. Methodology............................................................................................................13

3.1. The Theory.................................................................................................13

3.1.1. Five Factors of Personality Theory.............................................13

3.1.2. Hopeful Effect............................................................................15

3.2. Implementation..........................................................................................16

3.2.1. The model...................................................................................16

3.2.2. Decision Making.........................................................................17

3.2.3. Character Development..............................................................19

3.3. Evaluation..................................................................................................21

3.3.1. Methods of Evaluation................................................................21

3.3.2. The Test Application..................................................................21


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3.3.3. The Questionnaire.......................................................................21

3.3.4. The Personality Test...................................................................22

4. Results.......................................................................................................................23

4.1. Example Situations....................................................................................23

4.1.1. Decision Making........................................................................23

4.1.2. Personality Growth....................................................................24

4.2. User Experiences......................................................................................27

4.2.1. Questionnaire..............................................................................27

5. Discussion.................................................................................................................30

6. Conclusion................................................................................................................32

6.1. Summary....................................................................................................32

6.2. Future Work...............................................................................................32

References.....................................................................................................................34

Bibliography.................................................................................................................38

Appendices...................................................................................................................39

Appendix A: User Questionnaire.................................................................................39

Appendix B: Results.....................................................................................................41


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LIST OF FIGURES

Figure 1 | Artificial Neural Network................................................................................

Figure 2 | Overview of SPOT personality model.............................................................

Figure 3 | Variable Connections.......................................................................................

Figure 4 | Example Situation............................................................................................

Figure 5 | Character Variable deprecation rate.................................................................

Figure 6 | Personality Change Graph 1.............................................................................



Figure 9 | User Experience Results 1................................................................................

Figure 10 | User Experience Results 2..............................................................................




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LIST OF TABLES

Table 1 | 30 facets of the Big Five Personality Factors....................................................

Table 2 | Input Variables..................................................................................................

Table 3 | Decisions Made.................................................................................................

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1. INTRODUCTION

1.1. Setting the Scene

Imagine yourself playing a free roaming role play game where you have been

wreaking havoc in the local town by stealing goods, assaulting innocents, or even

killing some of the non-player characters (NPCs) who live there. People are running

around, screaming, all are very afraid of you, except for the one woman in the town

who is just standing there, content. You go over to her, and speak to her. She talks

about her missing son, and asks you to find him, not mentioning anything about what

you have just done in the street she is standing in; she is unfazed, she is scripted to

give you this quest, it is in the plot. This game has incredibly realistic looking

graphics, with large open worlds for you to explore, and amazing stories to discover.

However, no matter how good the game looks, there are always going to be those

scripted NPCs whose emotions, moods, or personalities are often times never

influenced by what is happening around them. Sadly, this is the case for many games

today, including Dragon Age: Inquisition (Dragon Age: Inquisition, 2014), Fallout 4

(Fallout 4, 2015), and GTA 5 (Grand Theft Auto V, 2013).

Now imagine the same situation, but that NPC is no longer standing there, she is

running and screaming and crying like the rest of them. Then, as you find her and talk

to her, she is terrified by what you have done, so you would have to prove to her again

that you are capable and trustworthy to do the task she has to give you. Imagine if she

never trusted you again, or maybe she is just as messed up as your character, loves

what you are doing to her fellow townsfolk, and decides to join in. This is how

realistic games should be, which is the main aim of the project; realism in NPC

personalities and choices.

1.2. Background

Recently, there has been a rise in popularity of open world, non-linear, free roaming

games, that have an emphasis on player choice and realistic worlds. Games like The

Legend of Zelda (The Legend of Zelda, 1986) and the Grand Theft Auto Series

(Grand Theft Auto, 1997) were amongst the first, and best non-linear, or open world


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games, where players are not forced along a path, but are encouraged to make their

own choices and stories and adventures. Games that are released in today's market that

are designed to be linear are often criticised for their lack of openness, or for being too

linear, for example Final Fantasy XIII (Final Fantasy XIII, 2009) (Peckham, 2010)

which is said to be "less like a roleplaying game and more like a battle simulator".

However, free roaming games are not all about the vast openness, and the exploration;

they are about the realism, the emersion, and making each persons' game experience

unique. This is where NPCs let the genre down. The non realistic, over scripted, and

just sometimes stupid characters are met in games often ruin the experience. For

example in the Assassins Creed series, where NPCs forget, within minutes, that they

just saw a man murder someone, and hide on a roof. (Reed, 2015)

This is where non-scripted NPC personality Artificial Intelligence (AI) may be able to

help. Firstly, the development time for scripted NPCs can be long, especially if there

are a lot of characters. A personality AI could cut this process out completely, by

implementing a decision making AI where one of the main input factors is personality.

In this way, a game can have hundreds of individual characters, by only changing a

few values. Of course, for story dependant characters more work and scripting will

still be needed, but with something like this implemented, there can be more

interesting characters than just the story centred characters. And with player choice

being such a big part of games, having these NPCs develop depending on the world

and their surroundings would be much easier with an AI system, rather than scripting

all possible situation, which would be impossible.

This kind of AI system could be used in many game genres, not only the above

mentioned free roaming games. RPG games, with their many interesting characters

and story, and obviously role-playing. Imagine role-playing along side a character

who is going to develop and learn from your interactions with it, instead of one who

has been scripted to act in some way. This also brings replayability, as the characters

can be randomised, so each time one plays the game it is not the same scripted

character. Really, any game with some characters, either in the foreground, or

background, could use a system like this to improve its realism, which is what most

genres want in today's market.


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1.3. Aims

This project aims to create an AI with personality and moods, that can live a realistic

life in a video game without the need for their lives to be fully scripted, as many more

story-centric characters are. To take it further, human moods and personalities are not

static; they are developed from birth. According to research over 40% of personality is

based on genetic influence (Bouchard, 1994), while the rest is being influenced by the

surrounding environment. So, knowing that, the second aim of this project is to have

these NPC personalities develop overtime to create the most realistic NPC possible.

The AI developed will be a decision making NPC that will be given different

situations to deal with, where the main inputs will be mood, emotions, and

personality. The personality description that will be used is one of the most recognised

in psychology today, the Big Five Factors of Personality (McCrae and John, 1991).

Many researchers have done similar things, but rarely are they related to video games.

Most are in connection to believable agents, their aims being to improve human-

computer interactions (Poznanski and Thagard, 2005) with things like ATM machines,

or self checkouts, though some research has been done into computer companions,

such as pets with personalities too (Mateas, 1998)

1.4 Research question

"How can learning AI be used in games to create more adaptive decision making,

leading to more realistic characters behaviours?"

Thus the project objectives shall be:

Develop an application that uses the five factor model of personality to

demonstrate how personality traits affect; mood, emotional state, and most

importantly, the decision making process.

Develop a component of the application to mimic the growth/change of

personality as it is effected by external (environmental) and internal (moods,

and relationships) factors.


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Evaluate how realistic/ believable the decision making process is by testing

against human decisions, and assess how viable this method is to use in

interactive video games, in terms of computational power.

At the end of the project it is expected that the system designed will be a realistic, and

useable method to be used in character development for games. The character will

hopefully take appropriate actions to situations, learn from past situations, and

develop to be an interesting and seemingly fleshed out character. Users of the

application are expected to enjoy the characters interactions, and believe in them as

much as, if not more than, current games where NPC decisions and actions have been

scripted.


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2. LITERATURE REVIEW

2.1. Modern Video Games

2.1.1. The Interactive Media

Unlike books or movies that offers a different level of interactivity, “the video game

industry is now seemingly on the verge of securing a position of dominance within the

realm of popular visual culture.” (Garite, 2014) This popularity in games is due to

how interactive games are, as they put an “emphasis on the ‘active’ role of game

players "which makes the gaming world “both procedural and participatory" (Garite,

2014). As a result, “game players are thus seemingly granted a degree of agency and

choice,” something that books or movies can’t serve as a medium of entertainment

(Garite, 2014). A large part of this is due to the interaction with game characters that

are made to be as realistic as possible using a variety of Artificial Intelligence

techniques.

2.1.2 The Characters and Possible Techniques to Create Them

Video games would be nothing without the characters that inhabit the worlds

portrayed, and there are many ways that characters can be made to be interesting and

seem to be intelligent. This section will cover a few of the most common methods

used in games today to make NPCs more than just pretty faces.

Scripting is the most traditional way in which games implement interactions between

players and NPCs (Cutumisu, Et al. 2007), which works the same way as scripting in

filmsA character is told exactly what choice to make, where to go, and what to say.

This style of creating game characters is excellent for linear stories with little choice,

as the characters will always deal with the same situations in the same order.

However, there is very little variability to scripting, which makes it a huge problem

when making larger, open world games where the player is given choice (White, Et al.

2007). Not only that, but it takes hours and hours of work to script characters,

especially if there are a lot of characters.


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Other options include Fuzzy Logic systems, which is a decision logic based on

degrees of truth, rather than the usual true or fault that modern computers are based

on. (Rouse, 2006In games, this means that a character would make a decision based

on a set of rules, and input variables. For example, if health is low move further away

from enemy. (Kose, 2012) Of course more complex rule sets can be made, and a

character can become incredibly smart and tactical. This type of character AI is great

for a lot of game aspects, like movement or tactics, though it is not been used for

character personality or individuality. This does not mean it cannot be used for such

things, but in today's games it has not been seen in this area of AI.

Artificial Neural Networks (ANN) are another form of AI defined by Dr. Robert

Hecht-Nielsen as "...a computing system made up of a number of simple, highly

interconnected processing elements, which process information by their dynamic state

response to external inputs" (Caudill, 1987). ANNs are made of layers; the input layer,

where the network is given its input, the hidden layers where the processing is done

via a system of weighted connections, and the out layer which gives an answer.

Figure 1 | Artificial Neural Network (The University of Wisconsin Madison, 2004)

Most ANNs also contain learning, which modify the weights of the connection

according to the input patterns it is presented with (The University of Wisconsin

Madison, 2004). ANNs are used to create clever learning AI, and therefore may be


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perfect for game characters, but they are far to complex and memory expensive. This

means that it is nearly impossible to justify having any sort of ANN in a game system.

2.2. Real People

2.2.1. Personality

Personality is at the core of every human being, without it humans would be like

robots, with no preferences, and nothing that makes us different. With that in mind

what better way to make an AI seem more human than giving it an artificial

personality. Otto Kernberg defines personality as "the human organism's capacity to

experience subjective states that reflect the internal condition of the body as well as

the perception of the external environment within which the body functions."

(Kernberg, 2016). To put it another way, personality is reflecting ones perception of

experience and external stimulus by the way one thinks, acts and makes choices.

However where this personality comes from has been hotly debated for many years.

The two most argued origins are genetics, that ones individual personality is all

encoded in their genes. “Although Galton discussed genetic influence on personality,

the lack of reliable and valid measures of personality qualities hampered progress. In

addition, until recently, psychologists could not agree on which were the important

traits of personality. (Bouchard, 1994) other position of argument is that of

environment, that your upbringing, surroundings and experiences define your

personality from a young age.

Recently most personality researches have come to the same conclusion, "most likely

that both genetics and experience in early childhood, in early family life, played an

important role, now, in who you are. All of it together comprises the basic seeds that

eventually accounted for the growth and appearance of one’s full personality.”

(Kellerman, 2012) If this is the case then can personality evolve and change over

time?


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"Despite the common perspective that personality traits—relatively enduring patterns

of thoughts, feelings, and behaviour— do not change, numerous longitudinal studies

have now reported mean-level changes in traits at various ages across the life course

how it changes." (Roberts and Viechtbauer, 2006)

Many research pointed towards the fact that personality only changed during

childhood, and the solidified, but recent discoveries argue that this is not the case.

Recent longitudinal and cross-sectional aging research has shown that personality

traits continue to change in adulthood." (Brent and Mroczek, 2009) This is a huge leap

in personality research and opens many doors to the AI community too, as this means

personality based AI models can now hopefully become more realistic with this

addition.

Now a major question to both AI developers and personality researchers is how to

represent this personality that is formed from genes, experiences, and can change as

one ages. Many methods have been used over the years, but now personality

researchers have come to agree on one method as the potential best method. The Five

Factor Model developed by Ernest Tupes and Raymond Christal.

“The Five-Factor Model has been widely accepted as an adequate taxonomy of

personality traits, and literature reviews are now routinely organized by classifiying

measures along the lines of these five factors. These factors - Neuroticism,

Extraversion, Openness, Agreeableness, and Conscientiousness… are basic

dispositions that, as we will see, endure through adulthood and help to shape emerging

lives.” (McCrae and Costa,. 2003)

With this definition of personality the AI community can now use it to create excellent

quality believable agents, and with research starting in this field in recent years it is

likely to emerge in the public eye relatively soon. This will be discussed later in

section 2.3.


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2.2.2. Choice

How people make choices is a very important research topic, not only in psychology,

but also in the research of artificial intelligence. There are many aspects that affect the

decision making process, for example, the "uncertainty about the consequences of

everyday decisions can make it hard to predict which option will prove best" (Caruso,

2006) Furthermore, "research shows that people often construct their preference in

the context of decision, and that nuances in the information that is salient at the time

of decision can dramatically influence choice" (Caruso, 2006).

Decisions are not concrete things and depend on a lot of factors that are present at the

time of the decision, but the main three that this project will look at are personality,

mood, and emotional state. “The idea that people actively choose to be in situations

that best ‘fit’ their personalities is hardly a novel concept. In fact, its relevance to the

matter of behavioural consistency has long been recognized by personality theorists,”

which shows how important the use of personality is in a decision making AI (Ickes,

Snyder, and Garcia 2015)

In fact, it is believed by many personality researchers that "personality-based

variations in behaviour are largely interpretable," which makes a huge importance to

the AI community as being able to interpret and understand these behaviours could

lead to using personality as a basis of decision making system, and ultimately

developed an AI with truly realistic behaviours.

(Paunonen, 2003).

It is widely recognised that mood can affect the decision making process. Shanfir and

Caruso completed four studies on the impact of mood on people’s choices, saying,

"Mood often provides such information, and can play a vital role in preference

construction as people attempt to determine which option will feel most appropriate

given their affective state and motive." They also hint at some distinct differences

being in good, neutral or bad moods can have on decisions, for example, "bad mood

among dieters and anxiety in obese people can cause them to eat more." (Caruso,

2006)


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Other researchers have also found a correlation to mood and decisions made, for

example Yuen and Lee have done extensive research on the effect mood has on

decisions based on risk taking, and discovered that “positive mood was expected to

increase the risk-taking tendency According to the Affect Infusion Model (AIM),

heuristic processing would be adopted by participants in positive mood." (Sung Lai

Yuen, 2003)

Mood also has a direct correlation to emotions, as a person in a bad mood is unlikely

to be happy, and a person in a good mood is unlikely going to be afraid, and research

directly shows how specific emotions correlate to decision making. Norbert Schwarz

who published Emotion, Cognition, and Decision Making, found that

“Extending the feelings-as-information approach to specific emotions,

[Bettman and Payne] propose that judgements and processing

strategies are likely to reflect the appraisal-tendency underlying the

emotion at hand. Consistent with this notion, they demonstrate, for

example, that two negative emotions, fear and anger, may affect

judgements of risk in opposite ways: Whereas fearful individuals made

pessimistic judgements about future events, angry individuals made

optimistic judgements. “ (Schwarz, 2000)

Again, this shows that emotions affect the decisions made and human’s thought

processes during their current situations.

Human decision making is a very complex thing, but it is rational, and understandable.

Being in a specific situation is going to have an effect on a person’s mood and

emotional states, which also have corresponding effects on each other. Personality

also determines how one will react to situation in a practical and emotional way.

Together, these four variables are the basis by which humans make basic situational

decisions; current situation, personality, mood, and emotional state.


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2.3. Creation of Personality

2.3.1. Uses

Current developments in believable agents with personalities and emotions have been

brought to all areas of computing. Imagine self service checkouts with a computer

intelligence to talk to you, or a robotic pet with a realistic personality to keep you

from getting lonely. These are some of the ways believable agents are being used

today, but they also lend themselves to being used to create realistic NPCs in games.

2.3.2. Research

Ever since there have been stories, there has been a quest to create believable

characters, meaning a character who will give the reader, viewer, or listener the

illusion of life (Bates, 1994). The media of computer games is still somewhat young,

still finding its footing in the world of story-telling. The ways of literature and film

have been used to create lovable, weird, and hated characters in games, but with such

a complex medium there are many other ways to create great characters for games.

AI, "the development of computers that are able to do things normally done by people

-- in particular, things associated with people acting intelligently" (Hammond, 2015),

is something games can use that no other entertainment medium can. In fact Alex

Champandard believes "compared to standard scripting techniques, AI technology can

be computationally more efficient and can generate better quality behaviours."

(Champandard, 2004). However, making a 'true' AI is a huge task, and actually is not

needed many gaming applications. AI in games rarely needs to know how to drive,

and how to play chess. This type of AI is sometimes called Artificial Narrow

Intelligence (ANI), named as such because of its narrow specialization (Andros,

2015). It is used in; racing games to navigate the road, military games for enemy

tactics and aiming, and arcade fighting games to make fighters learn tactics. It can be

used to create any type of character in any genre of game.

Believable agents are a type of AI that are developed to be relatable and feel like the

user is interacting with another human, rather than a computer (Loyall, A 1997). So


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this is the perfect kind of AI to be used for NPCs, as that is precisely what the user

wants to believe; the character they are interacting with is real (Umarov and

Mozogovoy 2012). A believable agent for gaming applications has to be

computationally inexpensive, yet as realistic as possible.

2.3.3. The Future

The future of believable agents, not only in games, is a bright one. The book, 'The

Emotion Machine' by Mavin Minky talks extensively about how the future of

machines may be very similar to humans. He talks about love, pain, common sense,

resourcefulness, and even recognition of self in machines!

" I hope this book will be useful to everyone who seeks ideas about how

human minds might work, or who wants suggestions about better ways

to drink, or who aims toward building smarter machines. It should be

useful to readers who want to learn about the field of Artificial

Intelligence. It should also be of interest to psychologists, neurologists,

computer scientists, and philosophers because it develops many new

ideas about the subjects those specialists struggle with." (Minsky, 2006)

Some of this is very science fictionesque, but as research continues and AI is able to

develop further, it is not hard to believe that one day there may be machines that walk

around and interact with humans, just like in films like i-robot or games like Destiny.


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3. METHODOLOGY

3.1. The Theory

3.1.1. Five Factors of Personality Theory

In the study of personality and behavioural science, there have been many ways used

to describe one's personality, but it is widely agreed upon that the Five Factors of

Personality is one of the most accurate and useful manners in which to measure or

describe personality (McCrae, 1991). The Five Factor model, as shown in table 1, is

made up of openness, conscientiousness, extraversion, agreeableness, and neuroticism

(OCEAN). Each one of these factors is used to describe different parts of a

personality, shown in the second column of the table.

The categories of OCEAN can therefore be matched with a series of actions and

responses to external events, meaning with some surprising accuracy one can predict

actions based off of a personality profile like the five factor model (Epstein, S. 1979).

The actions matched with each factor of OCEAN is widely theoretical, but many

researchers come to very similar conclusions, and as such the actions most often found

to be associated with a factor were chosen in this project.


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Table 1 | 30 facets of the Big Five Personality Factors (Jang and Livesley, 1996)

Openness Imagination

Artistic Interests

Depth of Emotion

Willingness to Experiment

Intellectual Curiosity

Tolerance for Diversity

Conscientiousness Sense of Competence

Orderliness

Sense of Responsibility

Achievement Striving

Self-Discipline

Deliberateness

Extraversion Warmth

Gregariousness

Assertiveness

Activity Level

Excitement-Seeking

Positive Emotions

Agreeableness Trust in Others

Sincerity

Altruism

Compliance

Modesty

Sympathy

Neuroticism Anxiety

Angry Hostility

Moodiness/Contentment

Self-Consciousness

Self-Indulgence

Sensitivity to Stress


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3.1.2. Hopeful Effect

The application will involve a decision making believable agent. This will incorporate

personality using the five factor model; emotions and mood. Input will be the event

statistics that the agent faces, and the output will be the decision made, in a similar

approach that Poznanski and Thagard did in their application (Poznanski and Thafard,

2005).

Figure 2 |Overview of SPOT personality model (Poznanski and Thafard 2005, p.228)

Figure 2 shows the influences between components Poznanski and Thagard used,

which is the way the same as this project, excluding the relationship component.

Weighing for each components were tested and refined during the creation of the

application, and starting values for each component are decided by the user on start

up. There will be a set of 7 types of events, and 9 possible choices, with contextual

story layered on top for different events.

After each choice, the values change based on what choice was made, and how much

these values change was refined and tested to achieve something that felt as realistic

as possible.

The end goal and hopeful effect of this decision making process was to discover if

using OCEAN as a basis for a decision making AI in games. Also, whether the

development of such a personality would be realistic, and computationally viable for

games. It is hoped that the simulated development of personality will improve NPC

realism, above other non-developing NPCs, for the future of games AI.


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3.2. Implementation

3.2.1. The model

The model being used in the project is very similar to the above example in figure 1.

Inputs are situations, personalities, emotions, and moods, and the output is the chosen

action. Each parameter has an initial value from zero to one, and is then weighted to

each action. All of these individual weighted values are added together for each

action, and the action with the highest value is chosen. Once an action is chosen, the

parameters that are linked to that action are increased in value to strengthen that

choice, and make it more likely the next time, to represent growth in the character.

These growth stats then depreciate overtime — closer to the base value again to model

the way immediate choices are affected more than future choices after specific events.

For example, if one has a fight with their wife, their anger value will be higher for a

while, which means that anger is going to have a higher influence on their next

decisions for some time. However, as time goes on, their anger will decrease, and

eventually will level out and have less influence on their decisions, which is identical

to personality and mood, although the depreciation speed is different for each. This is

why to achieve a realistic character, it is necessary to refine and test each value's

depreciation speed, then adjust them accordingly.


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3.2.2. Decision Making

Table 2 below, shows all the input variables, and figure 2 shows how they are

connected to one another and with the output decision.

Personality Emotion Mood Event

Openness Neutral Neutral Neutral

Conscientiousness Happy Good Friendly

Extroversion Sad Bad Hostile

Agreeableness Angry Help

Neuroticism Afraid Explore

Curious Persist

Stress

Table 2 | Input Variables

Figure 3 | Variable Connections

Figure 3 shows the basic connections between groups of variables, including how

personality affects both the emotion and the chosen action of the character, how both

event and mood affects emotion, and how emotion only affects the action. Although,

not all moods would connect to all emotions, for example, the only moods that are

connected to emotions are Good to Happy, and Bad to Sad and Angry. The same goes


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for all connections, only specific variables in each heading is connected to other

variables.

To explain this a little more with an actual example, suppose a character has only

openness in their personality, is in a good mood, and is currently in a neutral

emotional state. This character has to deal with an explore event. Figure 4 explains

how this interaction would work out.

Figure 4 | Example Situation

The orange nodes are the initial state nodes, the green nodes are ones that are activated

because of connections, and the red one is the action chosen. Each line represents a

connection, and each connection has a weighting value, for example if openness is set

at 1, and the weighting to the curious node is 0.5, curious becomes 0.5 times 1, which

is 0.5. In addition, any another nodes connected to curious would be added on top of

that, and then the final curious value is transferred to its connections.


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In this simple example there is only one initial node in each section, but the

application can have all nodes in every section active. This excludes the event section

as only one event happens at a time. The end product creates a complex network of

connections, producing what is hoped to be a believable and correct choice.

3.2.3. Character Development

After the initial set up of a character where values are restricted to stay between one

and zero, once the character development module of the application is turned on the

character can change its variables to exceed the upper limit. Once the character makes

a decision, like the one described in the last section, the character changes based off of

the factors that made the decision. Using the example situation in figure 3, all nodes

that are connected to 'explore', which influence that decision, will now change by a

degree. This number is different depending on whether it was a personality node,

mood node, or emotion node (the event nodes do not change as they are unique with

each situation and are not part of the character model).

This means that if a similar situation comes up again, all of these factors are now

stronger, which suggest that these factors will have more influence than others, and

might lead to the same decision made again. However, as it is described before in

section 2.2.1, personality doesn't change in this manner and these factors also would

not grow in a similar fashion. So, to model this more realistically these changes are

not permanent.


- 20 -

Figure 5 | Character Variable deprecation rate

Figure 5 shows the relative deprecation rate of the character's three characteristics.

Personality changes the least, and deprecates the slowest, while emotion changes the

most and deprecates the fastest. According to the Oxford dictionary, the three are

defined as; personality — the combination of characteristics or qualities that form an

individuals distinctive character, mood — a temporary state of mind or feeling, and

emotion — a strong feeling deriving from one's circumstances, mood, or relationships

with others . Based on these three definitions, it is clear how long each change would

likely last.

In practice, this means that for every decision made, the character is going to change

emotionally a lot, but will settle back close to their natural state very quickly. Where

as their personality will only alter slowly, but the changes will last a lot longer. The

personality factors never go back to their original value, to show the evolution of

personality over time.


- 21 -

These changes are to represent a realistic state of human characteristics and the way

they are influenced by situations. Though there are many more factors to take into

account in real life situations, these are considered major contributors by

psychologists.

3.3. Evaluation

3.3.1. Methods of Evaluation

Methods of evaluation that have been used for this project include personality tests

and user experience questionnaires. Personality tests were used to measure the

accuracy or realism of the AI responses with quantitative data, and the user experience

questionnaires were used to measure the quality of the responses with qualitative data.

3.3.2. The Test Application

The application is a tablet application which puts an AI character against different

types of situations, with 'flavour' text on top to describe the situations in simple

paragraphs. The user will input a personality, mood, and emotional state into the AI

with sliders. Each variable has a description of what it means to help the user

understand how it might effect the AI's actions.

The user is then shown a board of face down cards, and a board game piece. They

move the piece along the cards one at a time, choosing its path. Each card is a new

situation, and when the piece moves, the card flips over to reveal the situation. The

user reads the situation, then reads what the character did to deal with the situation.

Once completed, they pick a new card until they reach the end of the board.

3.3.3. The Questionnaire

The first evaluation method was user experience questionnaires. The questionnaire

was designed to reveal which if either of the two AIs, with and without character

development, felt more relatable and realistic to the participant. A number of the

question on the survey used the Likert scale (Likert 1932) to measure participant's


- 22 -

opinions. The questionnaire can be found in Appendix A at the end of this paper.

3.3.4. The Personality Test

Personality tests were used complete by willing participants to acquire realistic

personalities to put through the program. The specific personality test used is called

the "Five Factors of Personality Test" (Psychologist World, 2016). This test gives the

participants personality scores in percentages which can then be inputted into the

application. The participant is then asked to complete another test, which is a list of

situations, the same as which the application can deal with, along with some extra "red

herring" questions for some quality control. (Presser, et al. 2004). These questions are

designed to stop the participant from answering in patterns, and also to "identify those

who fully read and engage in the survey" (Marketing Research Advisor, 2015)

The application is then ran to see how closely the AI's choices are to the participants

choices in the second test. With the results making it clear if the AI is acting

realistically or not.


- 23 -

4. RESULTS

4.1. Example Situations

4.1.1. Decision Making

In this section, the results of the decision making will be discussed. To test this, each

situation was tested 25 times with the five factors of OCEAN being set randomly

between zero and one. The resulting action was recorded.

Action

Explore Persist Talk None Avoid Help Insult Assault Cry

Sit

uati

on

Neutral 5 20

Friendly 9 7 1 7 1

Hostile 11 8 4 2

Help 4 3 2 16

Explore 23 1 1

Persist 12 3 4 5 1

Stress 4 9 6 2 4

Table 3 | Decisions Made

Table 2 shows the results of the 175 tests ran. Most of the tests concluded in

reasonable results, where the character chose a suitable action to the situation, but

there are a few outlying results, including the 'friendly' event that resulted in a 'cry'

action. This is a very unlikely reaction, and is only going to happen if the 'neuroticism'

factor of personality is extremely high, which it was not in this test scenario.

There are also a few other outliers which are odd decisions that don't make sense, for

example the 'talk' action in an 'explore' situation. The 'explore' situation is one which

the character has been asked to go do something or find something. So, to simply talk

to the quest giver does not solve or finish this interaction, which is quite a large

problem.


- 24 -

4.1.2. Personality Growth

Following are a series of graphs that show the five factors of OCEAN and how they

changed overtime with different starting positions over a series of 10 situations.

Personality Change

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1 2 3 4 5 6 7 8 9 10

Choices Made

Pers

on

ali

ty V

alu

e

Openness

Concientiousness

Extraversion

Agreeableness

Neuroticism

Figure 6 | Personality Change Graph 1

In figure 6, the starting positions were random, and the events were chosen randomly.

As shown, the personality grows faster than it depreciates, and never go back to its

initial value. This was how the application was planned to work, so this test was

successful.


- 25 -

Personality Change

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

1 2 3 4 5 6 7 8 9 10

Choices Made

Pers

on

ali

ty V

alu

e

Openness

Concientiousness

Extraversion

Agreeableness

Neuroticism


In figure 7, initial values were all set to zero, and again events were random. Again,

this example shows how the growth is faster than the deprecation, and as planned, the

values only depreciate when they are not being used in decisions, which is how the

growth of personality is shown to work in personality research. Though it may grow a

little fast.


- 26 -

Personality Change

0

0.5

1

1.5

2

2.5

1 2 3 4 5 6 7 8 9 10

Choices Made

Pers

on

ali

ty V

alu

e

Openness

Concientiousness

Extraversion

Agreeableness

Neuroticism


In figure 8, all starting values were set to their maximum of one, and events were

chosen as hostile and stressful for the first seven tests, then random for the last 3. This

was done as the 'neuroticism' factor is not used that often in other tests, so it was

necessary to check if it would grow and deprecate as the others did.

After running all the tests, adjusting the values, and conducting the tests once again,

the final results show how the application has worked as planned, though it was

logically flawed. From looking at these graphs and the situations that arose, especially

figure 8, one would imagine that when a person is dealing with stressful and hostile

situations, their extraversion — and possibly other factors like agreeableness — would

decrease in value, but this was never a part of the planned application. After testing, it

is evident that the character was just as open to help another character when they are

stressed or after being attacked, as when they were having a great day. This seems to

be quite unrealistic as one would think that the character would not trust anyone after

situations like that.


- 27 -

4.2. User Experiences

4.2.1. Questionnaire

Following are some graphs showing some of the questions that were filled out by

testers. More results are in Appendix B. The participants were a mixture of people

with a lot of gaming experience and some with basically none.

Enjoyed Overall Experience

0

1

2

3

4

5

6

7

8

Strongly Disagree Disagree Neither Agree Strongly Agree

Figure 9 | User Experience Results 1

Figure 9 is a promising graph as it shows that 14 out of 16 people enjoyed the

experience. From this small amount data, if the technique was implemented into an

actual game, together with more work and polish, it may be good for the user

experience of the game, however a larger test base would be needed to confirm this

assumption.


- 28 -

AI choices were in line with Personality

0

2

4

6

8

10

12



Figure 10 shows that the participants agreed with how the AI was acting, as the

choices the AI made met the participants' expectations. Meaning from a users

perspective the AI is fairly realistic.

Character Developped over time

0

1

2

3

4

5

6

7



During the testing, eight of the participants had the character development turned on,

and eight did not. The graph in figure 11 shows that the character development was

definitely noticeable to the participants, while those who did not agree or said neither

were those who did not have the character development turned on. Interestingly, one


- 29 -

of the participants without the character development strongly agreed with this, which

might seem odd, but as they did not have any gaming experience, it is possible that

they did not know what to expect.

Changing starting Personality changed Characters Decisions

0

1

2

3

4

5

6

7

8



For the participants that tried the application more than once, they were asked if the

different starting personalities actually made the character feel different. Figure 12

shows that the majority did agree that it changed the character, which proves the

usefulness of this technique, as it shows that it is possible to make different characters

with only five variables. Along with the other questionnaire data, it seems that these

characters will also be fairly realistic and enjoyed by the users.


- 30 -

5. DISCUSSION

This project set out to answer the question:

"How can learning AI be used in games to create more adaptive decision making,

leading to more realistic characters behaviours?"

Now that the results have been acquired after the completion of the project, it is time

to discuss whether or not this questions has been answered, and to what extent

learning AI can be used in games characters.

The first discussion is whether learning AI can be used to create more adaptive

decision making.

From the results shown in section 4 and in Appendix B, it can be seen that the Five

Factor Model of personality can indeed be used along with emotion and moods to

create a decision making AI. Users were overall happy with their interactions with the

application, which shows that this method of AI could be used in games and other

applications, as user experience is a major part of any game.

The AI is adaptive in multiple ways. The first of which is that the AI personality,

mood, and emotion can be set to different starting values, effectively making multiple

characters. Since users and the quantitative data agree that the characters acted

differently depending on the data given to the character at the start of the application,

this proofs that the AI is capable of being adaptive for many characters. This is great

for games, as it allows for many characters to be made unique with simplicity, and

without the need for hours of work, which is the case for scripting characters.

The second part of the question that asks whether this may lead to more realistic

characters behaviours is a harder thing to discuss, as it has a lot to do with the

individuals' perception. Though the majority of the participants enjoyed and agreed

with the decisions made by the character, there were a few cases that could be deemed

as wrong.


- 31 -

It was also discovered that the decision to make the personality factors never

depreciate below their starting value was incorrect, as it is possible to have personality

factors become less relevant to the entire personality as a whole. This was overlooked

during the planning phase, and did not arise until the review of results. It is possible to

add this functionality to the application with relative ease, but the testing and retuning

of the AI would take a large amount of time.

Overall, the AI does change over time, and this can improve their choices which

makes them more realistic, but without the addition of factors being able to depreciate

to below their initial values the model is flawed. However, the basic decision model

still works, but definitely needs improving as there are too many outlying choices that

leave the situation open. To combat this, the model needs to be able to make multiple

decisions during situations. Also, these situations need be more complex and yet still

flow smoothly, as situations are not just one thing but series of smaller things.

Ultimately, the application design was oversimplified to create the standard of realism

that was wanted.


- 32 -

6. CONCLUSIONS

6.1. Summary

From the results it is evident that the application only answers half of the question at

this time.

"Can learning AI be used in games to create more adaptive decision making?"

Yes.

"Can learning AI be used in games to create more realistic characters behaviours?"

Possibly.

It has been found that the five factors of personality, moods, and emotions creates

believable characters not only for games, but many other applications that may need

such a thing, for example self service checkouts. However, for this to be used in

games, the set up of the situations needs to be changed from singular events to a series

of events and decisions, so the character cannot leave a situation unfinished, or

unsolved. It is important to note however that in a story based game - which is the

kind that this application was designed to improve - the character would need to

constantly face different situations, which may overwhelm the model. However, this

model can serve as a proof of concept that personality is a great way to create

believable characters without scripting.

As for the development of this character, this model has shown the proof of concept

to be a realistic way of achieving character personality growth. The development

process just needs more complexity, mainly in the removal of limiting the traits from

lowering below their initial values. Allowing for the lowered personality traits may

create a much more robust and realistic agent for characters in games.

6.2 Future Work

Believable agents are an important topic in which a lot of research is currently going

into, not only in the games industry, but in many other industries out with pure

entertainment. To achieve a truly realistic computer personality is a long way to go,


- 33 -

but as this field of study continues to develop, it is likely that soon games will no

longer have massive amounts of prewritten content, in both characters and stories. The

game world could become self contained with no need of any scripting, and creating

believable decision making characters is the key to achieve this monumental goal. In

fact, if characters have a full set of personality, it could be possible to have a game

where the characters can create unique stories themselves without the need for any

story to be written.

As for now, believable agents are becoming more and more realistic, with

personalities, moods, emotions, as it is depicted in this project. Some go even further

by adding goals and even memories to help them become realistic and believable.


- 34 -

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APPENDICIES

Appendix A: User Questionnaire

1. Have you played many story based games or simulators before?

() () () ()

Never Rarely Occasionally Often

2. I enjoyed the overall experience.

() () () () ()

Strongly Disagree Strongly Agree

3. I thought the AI choices were in line with the personality I chose.

() () () () ()


Please give examples of what you deem to be unrealistic choices:

4. I was overall satisfied with the AIs performance

() () () () ()


5. I felt that actions characters took made sense to me.

() ()

Yes No

If not, can you describe why, or give an example?


- 40 -

6. The character felt realistic in comparison to other games experiences

() () () () ()


7. The character seemed to develop as it made decisions

() () () () ()


8. If you played more than once, did different personalities and moods feel different in

the decisions made?

() Only played once

() () () () ()

Very Different Very Similar

If you have additional comments please leave them below.

- 41 -

Appendix B: Results

Participant Number

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Ques

tion

1 4 4 4 4 3 3 3 3 4 4 3 2 2 3 1 2

2 4 4 5 4 5 4 5 5 3 4 5 4 5 4 5 3

3 4 4 4 4 4 4 5 4 4 3 4 4 5 5 4 3

4 5 4 4 4 4 4 5 4 4 3 4 5 5 5 4 3

5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

6 4 3 4 4 5 3 5 4 3 4 4 5 4 3 5 3

7 3 4 4 5 5 4 4 4 3 2 2 1 4 2 1 3

8 5 4 4 5 0 3 4 5 4 4 0 0 4 4 5 3

Have you played many story based games before?

0

1

2

3

4

5

6

7

Never Rarely Occasionally Often


- 42 -

Satisfatction with AI performance

0

1

2

3

4

5

6

7

8

9

10


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