Reading #5:  A twin strike of short gaming articles

Part 1:  Experimental Investigation of Human Adaptation to Change in Agent’s Strategy through a Competitive Two-Player Game

Introduction

This paper was written by researchers in Japan.  After reading the article, I found out that the primary researchers' webpages are in Japanese, so I can't really make anything of it...

Kazunori Terada, Gifu University: http://www.elf.info.gifu-u.ac.jp/terada/programming/jikken3/grab_v4l2.html

Seiji Yamada, National Institute of Informatics:  http://www.nii.ac.jp/en/faculty/digital_content/yamada_seiji/

Akira Ito, Gifu University, is an English student, so his page is legible.  However, he seems to be an undergrad, so there isn't really anything to write:  http://www.otago.ac.nz/profiles/otago000603.html

Summary

There is no denying that all humans adapt when competing with another individual.  This paper was simply a study to determine how human adaptation was affected when competing with humans vs. competing with computers.  

Related Work

I will do five pieces of related work here because a.) i'm doing two articles, and b.) the paper states that not very much research has been done in this field:

A paper on humans and game strategy: http://www.jstor.org/stable/10.2307/2098880

On changing strategy in a game:  http://www.sciencedirect.com/science/article/pii/S0899825685710305
paper highlighting the importance of intelligent AI in games:  http://www.aaai.org/ojs/index.php/aimagazine/article/viewArticle/1558
About changing strategy in games where not all information is known (such as the game in this study):  http://www.jstor.org/stable/10.2307/3689430
Changing AI strategy in games that are more complex than the one in this study:  http://www.dtic.mil/cgi-bin/GetTRDoc?Location=U2&doc=GetTRDoc.pdf&AD=ADA385122

These articles largely deal with strategy in games much like this one.  This paper is different in that it compares strategies that people form vs humans or machines.

Evaluation

The researchers formed two hypotheses:

     1.  An adaptation phase exists when a human is confronted with a change in the opponent’s strategy.

     2: Adaptation is faster when a human is competing with a robot than with a human.

These hypotheses were tested by having the subjects play a penny matching game vs a computer.  Half the players were told it was a computer, and the other half were told they were playing vs a human.  For the penny game, each side would choose heads or tails on a penny.  If the pennies matched, player A received both pennies, if they differed, player B got them both.  Ten games were played, with six rounds each.  In the 6th round of each game, the payout was 20x.  The computer used the exact same strategy vs all players, with a permanent change in strategy in the 4th round.  Below shows the percentage of wins in the sixth round.

The researchers' hypotheses were accurate, with one additional fact: in the 7th game, those playing against a human appeared to expect another change in strategy, when there wasn't one.

Discussion

This study helps AI designers to understand people's perception of computer opponents.

The paper acts like this is a novel study, but this seems significant enough to have been done before.  By significant, I mean important enough for game creators to look into.

Part Two: Through the Azerothian Looking Glass: 

Mapping In-Game Preferences to Real World Demographics

A paper about World of Warcraft

Introduction

This paper wasn't so much about CHI I think as it was just a census of World of Warcraft.  Regardless, useful information can be gained from such studies.  The authors are:  

Nick Yee, Palo Alto Research Center, has recently moved to Ubisoft, and is now studying gamer behavior.  Appropriate, given the nature of this paper.  http://www.nickyee.com/

Nicolas Ducheneaut, Palo Alto Research Center, has also moved to Ubisoft, and works with Nick Yee doing the same research.  http://www.linkedin.com/in/ducheneaut

Han-Tai Shiao, University of Minnesota, Twin Cities, is a graduate student working for the department of electrical and computer engineering.  http://www.umn.edu/lookup?SET_INSTITUTION=UMNTC&UID =shiao003

Les Nelson, Palo Alto Research Center, has worked on a number of inventions with Xerox.  His work has led to 2 products, 20 patents, and several publications in HCI.  http://www.parc.com/about/people/136/les-nelson.html

Summary

Massively multiplayer online role playing games (MMORPGs) are a huge source of data (among other things).  The purpose of this paper was to conduct a large survey/census, which would allow conclusions about the playing habits of certain demographics.  Ultimately, it will reveal what makes WoW such a popular game.

Related Work

These five articles are similar to this article because they deal with people in MMOs, and in one case, using MMO demographic information in games (EXACTLY like this article)

A study to see why people enjoy playing online games more than others:  http://online.liebertpub.com/doi/abs/10.1089/cpb.2006.9.772

A paper written by Nicolas Ducheneaut that seeks to explain the social behaviors of people who play MMORPGs. http://www.springerlink.com/content/n00107m734617388/
A report on the potential of using MMORPGs for demographic purposes:  http://www.mitpressjournals.org/doi/abs/10.1162/pres.15.3.309

Why people play MMORPGs at all: http://online.liebertpub.com/doi/abs/10.1089/cpb.2006.9.772

Paper about the type of people who generally like video games.  This is a much more general study than the one conducted in this paper:  http://www.amsciepub.com/doi/abs/10.2466/pr0.1984.55.1.271

Evaluation

The study called for 1000 volunteers to provide demographic information, and allow the researchers to collect character information for each person.  Over the course of six months, the researchers ran a script that checked if each character was online.  This information, combined with the given demographic data and publicly available character data allowed the researchers to draw many conclusions.  They found that age, gender, work schedule, and marital status all had impacts on people's playing habits, and that different ages and genders preferred different activities.  All information was objective and quantitative, but the information inferred from it is objective qualitative.

Discussion

The only plausible use I could foresee with this information is how to create a better game that appeals to a wider demographic.  This isn't particularly useful information for anything else, as far as I can tell.

Honestly, I'm not sure that this paper belonged at a CHI conference, whether it was interesting or not.