Game Development Reference
In-Depth Information
And so, the confidence information is transformed to suggestion weights. In City-
Lights, we used only two possible numbers of points per bet (one being a double of
another). We then directly used them as coefficients in tag
support
delta computation.
We consider the confidence mechanism as another way of using the information
about player's expertise in SAGs. We find it very viable for SAGs as it possess several
interesting features:
Betting is an attractive game feature that many game players appreciate.
It can easily be incorporated to almost any game. It is simply a matter of prompting
a player to place bet on action he is about to commence (whatever it may me).
It is a system that support itself, it requires no external information.
The system starts to work instantly with a new player, it does not require a longer
observance of the player (such as with the consensus ratio measurement).
Perspectively, the system can be used track also long term information on the
player's expertise. If for example, we had game tasks with known categories (e.g.
by sub-domain), we could measure longer term average confidence of the player
for each category, possibly exploring his “effectiveness” for only some of them.
References
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Multiagent Systems, Richland, SC (2011)
2. Roman, D.: Crowdsourcing and the question of expertise. Commun. ACM
52
, 12-12 (2009)
3. Seneviratne, L., Izquierdo, E.: An interactive framework for image annotation through gaming.
In: Proceedings of the International Conference on Multimedia Information Retrieval, MIR '10,
pp. 517-526. ACM, New York, NY, USA (2010)
4. Šimko, J., Tvarožek, M., Bieliková, M.: Creation of games with a purpose as tools for knowledge
acquisition: Little google game. Znalosti 2011 (In Slovak) (2011)
5. Šimko, J., Tvarožek, M., Bieliková, M.: Semantics discovery via human computation games.
Int. J. Semantic Web Inf. Syst.
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(3), 23-45 (2011)
6. von Ahn, L., Dabbish, L.: Designing games with a purpose. Commun. ACM
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(8), 58-67 (2008)
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