Holistic player modeling for controlling adaptation in video games

HOLISTIC PLAYER MODELING
FOR CONTROLING ADAPTATION
IN VIDEO GAMES
Boyan Bontchev
Prof. at Dep. of Software Technologies,
Fac. of Mathematics and Informatics,
Sofia Univ., Bulgaria
Marie Curie Fellow at Brainstorm Multimedia, Spain

Agenda
Introduction
Related works
The ADAPTIMES player model
Adaptation process
The “Rush for Gold” emotionally adaptive game
Case study
Preliminary results
Conclusions
2
9/04/2016Adaptation in Applied Video Games e-Society’2016

Player-centric adaptation
Player-centric adaptation in video games needs to
answer some questions:
Who – player character structural and behavioral
changes => requires player modelling
How – how adaptation will be realized => requires
adaptive loop design
What – which game features can be adapted =>
requires adaptive gameplay design
Why – advantages of game adaptation => requires
analysis of outcomes in playability and learning results
3

Player modelling
Player modelling is crucial for realization of an effective
player-centric adaptation in both applied and
entertainment video games. It implies:
Observation of individual player’s behavior “from a
contextually omniscient view”
Construction and updates of a model of that player
based on observation, and
Intelligent game adaptation for tailoring the gameplay
to the individual player.
4
 Source: Magerko, B. Adaptation in Digital Games, COMPUTER, July 2008, pp.87-89.

Player model types
Behavioral player models - describe dynamic
processes of player behavior and deal mainly with
flow, motivation and immersion
Organizational player models describe properties of
player’s character, their attributes and facets and, as
well, interconnections among them with their time
and model space constrains
5

Behavioral player models 1/2
 Mihaly Csikszentmihalyi (1990) developed the fundamental
concept of flow as a process of optimal human experience. In
digital games - a balance between the inherent challenge of the
game activity and the player’s ability required for its execution.
6
Player skill
Challenge
Boredom
Anxiety

Behavioral player models 2/2
 Based on the flow theory, Gilleade and Dix (2004) stressed the
importance of three issues:
 motivation of the users: why they want to play
 experience and skills: how able are they to play
 detection: how to identify when change is necessary
 Sweetser and Wyeth (2005) presented GameFlow model for
assessing player enjoyment incl.: concentration, challenge,
skills, control, clear goals, feedback, immersion, and social
interaction.
 The dynamic relation between the effort and the demand level
was described as motivational intensity (Fairclough and
Gilleade, 2012) going through boredom (low effort because of
low demand), engagement (rising effort due to increasing
demand), zone (peak of achievable effort at the highest level of
demand), and overload – low effort due to excessive demand.
7

Organisational player models
 Bridging the gap between game design and pedagogy (Kiili, 2006):
 flow antecedents - challenge–skill balance, action–awareness merging, goals
of an activity, unambiguous feedback, and sense of control
 flow experience
 flow consequences - increased learning, positive attitude, exploratory
behavior, and perceived behavioral control
 Game adaptation determine the level of playability (Sánchez et al,
2009): satisfaction, learnability, effectiveness, immersion,
motivation, emotion, and socialization.
 Besides playability, game adaptation may be used for increasing
player competence in both playing and game-based learning
context. User competence model (Silva and Behar, 2015):
 psycho-cognitive abilities
 attitudes
 knowledge
8

Playing style models
9
Relationships between Honey and Mumford learning styles
and playing styles of ADOPTA (Bontchev, 2011) and Bartle
Honey and
Mumford
Learns by: ADOPTA Bartle
Activist hand–eye coordination, planning and
strategizing, problem-solving, teamwork
and the ability to think quickly
Competitor Killer
Theorist logically entering problems step-by-step,
with spatial awareness and verbal &
numeracy skills
Logician Achiever
Pragmatist planning, decision-making, testing
hypotheses, strategic thinking,
management skills
Strategist Explorer
Reflector Observing and watching reflectively Dreamer Socializer

The ADAPTIMES FP7 project
 ADAPTIve player-centric serious video gaMES
 ADAPTIMES aims at investigating how
cognitive abilities (the cognitive part),
psycho-emotional status (the affective part) and
playing style (the conative part – that of “desire, volition, and
striving”) (Schur, 1990)
 can be used in a
holistic approach
for efficient and
effective
player-centric
adaptation
10

Adaptation in
11

Workflow of emotion-based
game adaptation control
12
Implicit
Emotional
Indicators
(via sensors &
other devices)
Facial expr.
GSR
Heart Rhythm
ECG
EEG
Pressure
…
Change
Procedures
Time
Velocity
Acceleration
Route
Size
Defeat range
Luminosity
Contrast
…
Real-Time
Explicit
Player
Feedback
through
Adaptation
Control Panel
Analysis
Change
Visuali-
zation
Triggering
Events
on Behavior
Templates

Case study – Rush for Gold
 A 3D video game using adaptation based on player performance,
efficiency and emotional state
 Developed by using Brainstorm eStudio (http://www.brainstorm.es/products/estudio/)
 Allows implicit recognition of ADOPTA playing styles in order to validate
them to ones calculated by using self-report. The implicitly found style
will be used for automatic selection of learning content appropriate to
that style.
 Goal: to collect 12 bars of gold (bullions), which are flying, hidden or
inside logic puzzles needed to be solved, all located in a 3D Egypt
temple with enhanced audio-visual effects being object of adaptation,
as well.
 The player can use a Strategy Management Table (SMT):
 represents a table with three rows for planning numbers of bars of the
three groups available in the game
 contains data about average effectivity of performance for collecting the
gold bars of each group useful for building a strategy for optimal way of
play.
13

Rush for Gold
14

Player style measurement
Implicitly during play time of specific mini-game
Based on player’s metrics for specific game tasks:
Performance (result)
Efficiency (result/effort)
Task difficulty
Play time
15
Rush For Gold, part 2 -
https://www.youtube.com/
watch?v=aJe61bUDE40

Emotion-based adaptation in Rush for Gold
 The game adaptation control is at run time and implicit for the
player
 The adaptation control makes the video game aligned to specific
response patterns of individual players for bringing positive
effect on playability and learning outcomes
 The adaptation process runs in the context of the game and
aligns adaptable game features to player-centric metrics
showing:
player’s progress and performance
player’s emotions – emotions are inferred by face expression
analysis using a Web service accessing Face Analysis Cloud
Engine of SightCorp (http://sightcorp.com/)
 fear, surprise, sadness and disgust are applied for additional correction of
current difficulty of shooting and discovering tasks by using specific
thresholds of their levels
 when finding relatively high fear, sadness and surprise, task difficulty is
decreased, while the opposite occurs in cases of high level of disgust
16

Adaptable game features in Rush for Gold 1/3
1. Adaptive automation of game tasks (and feedback for next
experiments):
 explicit tasks - game objectives (to shoot/discover gold bullions
or to solve puzzles) adapt to the gameplay;
 implicit tasks - not explicitly stated by the game interface but
expected to be fulfilled:
maximize your skills in shooting, discovering, solving and strategic
planning of activities
collect as many gold bullions as possible
 player-driven tasks - created by the player thanks to his/her creativity
within existing limitations of given game mechanics and leading to so
called emergent gameplay
how to find best position for shooting (depends on gun high and
shooting angle)
how to explore the temple with changing visual properties
17

Adaptable game features in Rush for Gold 2/3
2. Dynamic Difficulty Adjustment (DDA):
 DDA by means of automatic level generation - uses methods for
procedural content generation
Logic puzzles have increasing dynamically their difficulty with
higher player results and vice versa
 DDA by means of adjusting level content, i.e. game items for player
interactions – means dynamic adaptation of level of inventory
interacted by the player for specific game context, according to
player’s skill acquisition:
Hidden billions are more difficult to be found with player
progress
Flying bullions change velocity & acceleration plus striking force
change with player efficiency as well with player´s emotions
18

Adaptable game features 3/3
3. Adaptation of audio-visual effects:
according player´s emotions and using thresholds for
happiness level, there are adapted :
ambient illumination change
focus and contrast of statues with puzzle panels
19

Experiment
Executed at Sofia University, Bulgaria, with 34
volunteers (average aged 27, SD=10; 18 men and 16
women)
They passed group explanation and demonstration
(20 min.), procedure of informed consent (translated
in Bulgarian, 15 min.), individual assisted trial (5 min.)
and, finally, unassisted game session to determine
their style of play (15-20 min.).
Half of the volunteers (N=17) played the game with
emotional adaptation switched on (forming the
experimental group), unlike the others (the control
group).
20

Preliminary results 1/3
The quiz reveal (five-level Likert scale from 1 to 5):
certain preference to play the game with emotion-based
adaptation (question Q1 average=3.9, sd=1.1)
positive appreciation of that adaptation of shooting difficulty
(Q2 average=4.0, sd=0.8)
the same for discovering difficulty (Q3 average=3.8, sd=0.7),
and brightness and contrast (Q4 average=4.1, sd=0.7).
No statistically significant improvements were found in
playing time and shooting performance with emotional
adaptation (because all players fulfilled the goal)
Statistically significant correlations between answers to
questions Q1-Q4 and some game metrics
21

Positive statistically significant correlations (0,34÷0,55)
between preferences to play with emotional adaptation
and shooting/discovering efficiency, discovering
performance and game session time reveal the beneficial
impact of emotional adaptation inside the experimental
group.
In contrary, significant negative correlations
(-0,38÷-0,51) between degree of liking emotional
adaptation of the difficulty and shooting/discovering
efficiency and difficulty can be explained by appreciating
emotional adaptation for making the game harder when
found higher disgust (decreasing player efficiency and
performance) or easier when found higher fear, sadness or
surprise (decreasing attained difficulty).
22

23
Metrics of solving are checked only for correlations
with adapted brightness and contrast, as they are not
emotionally adapted.
Adapted brightness and contrast are correlated:
positively to solving performance (because of attracting
player’s attention to the puzzles)
and
negatively to discovering performance (because of
attracting player’s attention to other objects)

24
Rush For Gold (playing style)
9/04/2016
Generated labyrinth
(maze game)
3D quiz game
(assessment)
3D puzzle
Adaptation in Applied Video Games e-Society’2016
Next steps

Conclusions 1/2
Player-centric adaptive game play possesses essential
advantages compared to the non-adaptive gameplay
The synergy of using player´s performance, emotions,
and playing styles is very promising
All they are identified in an implicit way at run time
and used for adapting game mechanics, dynamics and
audio-visual content .
25

Conclusions 2/2
The results reveal a promising and positive appreciation
of emotion-based adaptation and, as well, interesting
statistically significant correlations between such
adjusting of dynamic difficulty of tasks and player´s self-
report.
More experiments with real time player´s feedback on
adaptation use, additional self-reporting and qualitative
analyses are needed for revealing how such emotion-
based adaptations affect game playability and
antecedents, experience and consequences of flow (Kiili,
2006).
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Thank you for your attention!
Discussion
More info at: http://adaptimes.eu/
27

Holistic player modeling for controlling adaptation in video games

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