Play-Persona: Modeling Player Behaviour in Computer Games

More documents

Recommendations

Info

19. Jørgensen, A. H.: Marrying HCI/Usability and Computer Games: A Preliminary Look, Proceedings of NordiCHI, Tampere, Finland (2004) 20. Kim, J. H., Gunn, D. V., Schuh, E., Phillips, B. C., Pagulayan, R. J., Wixon, D.: Tracking Real- Time User Experience (TRUE): A comprehensive instrumentation solution for complex systems. In Proceedings of CHI 2008, Florence, Italy (2008), 443-451 21. Kort, J., Steen, M. G. D., de Poot, H., ter Hofte, H., Mulder, I.: Studying usage of complex applications. In: Proceedings of Measuring Behavior. Noldus IT (2005), 266-269 22. Kuniavsky, M.: Observing the User Experience: A Practitioner´s Guide to User Research. Morgan Kaufman (2003). 23. Longley, P.; Goodchild, M. F., Macquire, D. & Rhind, D.: Geographic Information Systems and Science. Wiley & sons (2005). 24. Mandryk, R., Atkins, M.S., Inkpen, K.: A continuous and objective evaluation of emotional experience with interactive play environments. In: Proceedings of CHI (2006. 25. Medlock, M.C., Wixon, D., Terrano, M., Romero, R.L., Fulton, B.: Using the RITE method to improve products: A definition and a case study. In: Proceedings of UPA (2002) 26. Mellon, L.: Metrics in MMP Development and Operations. Presentation at the GDC, Los Angeles, USA (2004) 27. Nørgaard, M., Rau, J.: User Testing in the Combat Zone. In: Proceedings of ACE, Toronto, Ontario (2007) 28. Pagulayan, R. J., Keeker, K., Wixon, D., Romero, R. L., Fuller, T.: User-centered design in games. In: The HCI handbook. Lawrence Erlbaum Associates (2003), 883-906 29. Pagulayan, R. J., Steury, K. R., Fulton, B., Romero, R. L.: Designing for fun: user-testing case studies. In: Blythe, M. A., Overbeeke, K., Monk, A. F. Wright, P. C. (Eds.): Funology: From usability to enjoyment. Human-Computer Interaction series. Kluwer Academic Publishers (2005). 30. Renaud, K. and Gray, P.: Making sense of low-level usage data to understand user activities. In: Proceedings of SAICSIT 2004, ACM Press (2004), 115-124. 31. Rouse, R. Game Design: Theory and Practice. Wordware publishing Inc. (2001). 32. Schultz, C. P.: Game Testing All in One. PTR (2005) 33. Swain, C. 2008. Master Metrics: The Science Behind the Art of Game Design. Presentation at NLGD Conference, Utrecht, Holland (2008) 182
34. Thompson, C.: Halo 3: How Microsoft Labs Invented a New Science of Play. Wired Magazine 15, 9 (2007) 35. Trappl, R., Petta, P.: Creating Personalities for Synthetic Actors: Towards Autonomous Personality Agents. Springer Publishers, Berlin (1997) 36. Tychsen, A., Canossa, A.: Defining Personas in Games Using Metrics. In: proceedings of Future Play 2008, Toronto, Canada. ACM publishers (2008), 73-80 37. Williams, D.; Yee, N., Caplan, S. E.: Who plays, how much, and why? Debunking the stereotypical gamer profile. Journal of Computer-Mediated Communication 13 (2005), 993- 1018 183
Page 1:
Play-Persona: Modeling Player Behav
Page 4 and 5:
4.2.3 PLAYER EXPRESSION 53 4.3 PEIR
Page 7 and 8:
ACKNOWLEDGEMENTS I would like to th
Page 9:
ABSTRACT This thesis proposes a fra
Page 12 and 13:
Analysis seeks to break down comple
Page 14 and 15:
Considering games as acts of commun
Page 16 and 17:
ensemble - the syntagm. Selection r
Page 18 and 19:
described in terms of likelihood of
Page 20 and 21:
ook: FLUX, published in 2008. This
Page 23 and 24:
2. A THEORETICAL FRAMEWORK FOR MODE
Page 25 and 26:
“positivism” and “anti-positi
Page 27 and 28:
with the game world based solely on
Page 29 and 30:
on that text. Later, Barthes introd
Page 31 and 32:
according to their mental state. Wh
Page 33:
Following the humanistic tradition
Page 36 and 37:
In most games it is not realistic t
Page 38 and 39:
ehaviour. Assessing assumptions on
Page 40 and 41:
Independently on the identity of ea
Page 42 and 43:
main focus of the brand has always
Page 44 and 45:
3.4 Play-persona as a lens (a poste
Page 46 and 47:
Figure 10: personality and subperso
Page 49 and 50:
4. CREATING EXPERIENCES The MDA fra
Page 51 and 52:
Play-styles are sets of isotopic ga
Page 53 and 54:
4.2.3 Player expression Player expr
Page 55:
Players will eventually understand
Page 58 and 59:
Combining both of these two approac
Page 61 and 62:
REFERENCES 1. Aarseth, E. (1997): C
Page 63 and 64:
52. Hunicke, R. LeBlanc, M. & Zubek
Page 65:
96. Wiggins, A. (2006): Data Driven
Page 69 and 70:
ARTICLE 1 - TOWARDS A THEORY OF THE
Page 71 and 72:
flow between the player, the avatar
Page 73 and 74:
6. The player constructs knowledge
Page 75 and 76:
are sets of rational, bodily, and b
Page 77 and 78:
ehaviorism asserting that a compreh
Page 79 and 80:
4.3 Origin of subpersonalities Acco
Page 81 and 82:
environment and the emanating subpe
Page 83 and 84:
flow line), one must increase the c
Page 85 and 86:
7.1 Explorer’s path FIGURE 5 Expl
Page 87 and 88:
the roof section, where he/she will
Page 89 and 90:
14. DE SOUSA, R. 2003. Emotions. In
Page 91 and 92:
ARTICLE 2 - DESIGNING LEVELS FOR EN
Page 93 and 94:
2 STRUCTURE OF A GAME LEVEL The fir
Page 95 and 96:
3.2 Symbolical Reading The movement
Page 97 and 98:
The hangar is open for workers and
Page 99 and 100:
gather info, spying through keyhole
Page 101 and 102:
6.2 Play-Personas I am going to def
Page 103 and 104:
The Butcher persona would have quit
Page 105 and 106:
ARTICLE 3 - WAVING EXPERIENCES: PLA
Page 107 and 108:
types" [12]. Personas are construct
Page 109 and 110:
esults in the relatively easy task
Page 111 and 112:
Crew actions schemas are: • Squad
Page 113 and 114:
choice given until the mark “poli
Page 115 and 116:
REFERENCES 1. Bozec, P. "My Everyth
Page 117 and 118:
ARTICLE 4 - WEAVING EXPERIENCES IN
Page 119 and 120:
In order to be able to take acti
Page 121 and 122:
persona could be narratively define
Page 123 and 124:
of non lethal, silent, and clean de
Page 125 and 126:
ARTICLE 5 - DEFINING PERSONAS IN GA
Page 127 and 128:
software is however limited in that
Page 129 and 130:
event sets, i.e. capturing metrical
Page 131 and 132: objects and entities within it. Eve
Page 133 and 134: metrics include tracking camera vie
Page 135 and 136: Figure 4: Example of interaction me
Page 137 and 138: looting is a play-style observed in
Page 139 and 140: players can choose between differen
Page 141 and 142: Play modes: Running, climbing, fall
Page 143 and 144: according to their positioning on a
Page 145 and 146: 14. Medlock, M.C., Wixon, D.; Terra
Page 147 and 148: ARTICLE 6 - PLAY-PERSONAS: BEHAVIOU
Page 149 and 150: experiences are evaluated and remem
Page 151 and 152: B) It is possible to infer user nee
Page 153 and 154: personas are hypotheses that emerge
Page 155 and 156: Expert Rookie Grunt Athlete Chess-
Page 157 and 158: Procedural description: Shooting: -
Page 159 and 160: In the case example for Tomb Raider
Page 161 and 162: 2. Cooper, A.: The Inmates Are Runn
Page 163 and 164: ARTICLE 7 - TOWARDS GAMEPLAY ANALYS
Page 165 and 166: The requirement for improving user-
Page 167 and 168: The literature on game metrics is m
Page 169 and 170: ecause they all stem from in-house
Page 171 and 172: If a player kills a traitor they re
Page 173 and 174: Figure 3 (Top): diagram showing the
Page 175 and 176: titles where there is a trend towar
Page 177 and 178: a secondary variable together with
Page 179 and 180: player spent at the location and wh
Page 181: 3. Börner, K., Penumarthy, S.: Soc
Page 185 and 186: ARTICLE 8 - ANALYZING SPATIAL USER
Page 187 and 188: on basic statistical analysis metho
Page 189 and 190: visualization or for creating overv
Page 191 and 192: egarding actions undertaken in-game
Page 193 and 194: ased methods within the games area
Page 195 and 196: 2.4 The EIDOS Metrics Suite The dat
Page 197 and 198: is played in Third-Person perspecti
Page 199 and 200: one cause of death, and performing
Page 201 and 202: ArcGIS permits different layers to
Page 203 and 204: 4. Cadez, I., Heckerman, D., Meek,
Page 205 and 206: 35. Whiteside, J., Archer, N. P., W
Page 207 and 208: ARTICLE 9 - PLAYER MODELING USING S
Page 209 and 210: unsupervised learning in capturing
Page 211 and 212: 3. TOMB RAIDER: UNDERWORLD The popu
Page 213 and 214: 2 - Environment; the percent of tot
Page 215 and 216: (ESOM) [5] to emphasize the distinc
Page 217 and 218: populated middle-left cluster (Fig.
Page 219 and 220: weight values we repeat the trainin
Page 221 and 222: TABLE I THE FOUR PLAYING BEHAVIOR C
Page 223 and 224: (d) Number of Deaths, D (e) Complet
Page 225 and 226: equests for specific in-game puzzle
Page 227 and 228: 13. G. N. Yannakakis and M. Maragou
Page 229 and 230: ARTICLE 10 - PSYCHOLOGY OF PERSONAL
Page 231 and 232: Personality is described as recogni
Page 233 and 234:
Inputs: Outputs: Primary attack (ra
Page 235 and 236:
Due to the fact that each game metr
Page 237 and 238:
12. Jennett, C., Cox, A.L., Cairns,
Page 239 and 240:
ARTICLE 11 - GAME METRICS AND BIOME
Page 241 and 242:
His research interests are biometri
Page 243 and 244:
5. R. L. Hazlett. Measuring emotion
Page 245 and 246:
ARTICLE 12 - ANALYZING USER BEHAVIO
Page 247 and 248:
elated to player-game interaction a
Page 249 and 250:
10. Kuniavsky, M.: Observing the Us
Page 251 and 252:
ARTICLE 13 - PATTERNS OF PLAY: PLAY
Page 253 and 254:
Play-personas are here introduced a
Page 255 and 256:
It is only natural that game design
Page 257 and 258:
4 Defining play-personas using game
Page 259 and 260:
TRU is the eighth installment in th
Page 261 and 262:
gameplay, descriptiveness of player
Page 263 and 264:
In the case of TRU, the three param
Page 265 and 266:
into which sections of the levels t
Page 267 and 268:
Runners: This group completes the g
Page 269 and 270:
17. Iser, W.: The Implied Reader. J
show all

Play-Persona: Modeling Player Behaviour in Computer Games

Create successful ePaper yourself

Delete template?

Save as template?