Classifying Players For Unique Game Experiences
togelius writes "Whenever you play a game of Tomb Raider: Underworld, heaps of data about your playing style is collected at Eidos' servers. Researchers at the Center for Computer Games Research have now mined this data to identify the different types of player behavior (PDF). Using self-organizing neural networks, they classified players as either Veterans, Solvers, Pacifists or Runners. It turns out people play the game for very different reasons and focus on different parts of the game, but almost everyone falls into one of these categories. These neural networks can now quickly determine which of these groups you belong to based on just seeing you play. In the near future, such networks will be used to adapt games like Tomb Raider while they are played (e.g. by removing or adding puzzles and enemies), so you get the game you want."
Just what we need... surround ourselves with ourselves. That will challenge us and cause us to grow into intelligent, tolerant and well rounded individuals.
-1 Uncomfortable Truth
I don't like the idea of BUYING something and then having my use of it monitored. That's no different than spyware.
Corporatism != Free Market
...15 years ago. They change the names and claim it as unique research?
No. Bartle's taxonomy is only really relevant for MMORPGs and MUDs. This one is mostly for first person shooters and similar games.
So, Veterans and Runners complete the game very quickly, while Pacifists complete the game faster than average. Seems those 22.12% which are Solvers are really bringing down the speed curve a lot here.
I like this take on it better:
http://insultswordfighting.blogspot.com/2008/01/new-taxonomy-of-gamers-table-of.html
The types are Tourist, Skill player, Completionist. Also, on a value scale, you can range from wholesale to premium.
"It doesn't take a rocket scientist" -I guess I should leave then
It would be interesting to see this in a strategy game like Civ 4. If you spend all your time in economics then the game will ease off the aggresive AI.
Of course just making the AI better would help a lot.
Common Sense
I personally think jumping puzzles exist because it represents a fear that doesn't need 'selling'. No one wants to fall down a hole, whereas that monster may or may not be 'realistic enough'.
But, once you've run your data through and decided that 4 categories are sufficient, most designers (including myself) will restrict the NN to those categories. And somebody with really weird behavior will get lumped in and will slightly skew the existing category. The guy who runs into a crowd and dies over and over again may be described as a Runner, but he'll be an outlier in the runner class and his behavior will tweak the definition of a Runner.
Your options are to ignore outliers like him to avoid polluting your class, add a new class for people with that kind of behavior if there are enough of them to justify it, or (most likely) just accept that outliers skew tight groups and lump him in as a Runner - If the group is tight enough and he's rare enough, it won't matter.
Ideally, however, your architecture will be flexible enough that you can weigh how good a fit each player is to each group and adjust accordingly. I.e. adjust every obstacle according to a best-fit weighting rather than just delivering 4 different options on each level. Not having played the game or reading TFA, I can't speculate on that front.
He's getting rather old, but he's a good mouse.
Mark Rosewater, current head developer of Magic the Gathering, explained a much more in depth categorization. It has a lot more "gray areas" (in which people act like one or the other at different times), but I find it a lot better than this description (at least for tabletop games).
You can find the original article here. The other articles are found here and here/
Ginga no Rekshiya Mata Each page.
subversive behaviors do not just represent outliers; it can be very interesting to look at players that don't fit clusters, these are the players that invented rocket-jumping and bunny-hopping, so it might be really interesting to look at "monkey-chasers", "spastic insomniacs" and all profiles not fitting the big clusters as they might be early-adopters.