I've been intrigued by a parallel I've noticed between games created by my students and some concepts from the Stanford AI class, e.g. partial observability
In general in some basic 2d games partial observability of the environment makes the game a lot more fun and I was just playing a sidescroller by one student that imported a somewhat similar mechanism to the old missile command arcade game, and I was wondering if one could create a game mechanism taxonomy like they have for AI agents/environments and use it to predict which sorts of game mechanism combination would be fun and which would not ...
http://www.ferzkopp.net/joomla/science-mainmenu-15/9-ferzkopps-philosophy-work/77-a-heuristic-taxonomy-of-computer-games
http://www.iexbeta.com/wiki/index.php/Video_Game_Taxonomy
but I'm thinking of something finer grained that might link up to the abilities and types of agents playing the games ...
It also makes me think about why watching certain types of sports are compelling. Watching people dodge each other seems to set off interest centers in our brain related to our evolutionary development; being able to dodge away from a sabre-tooth tiger being highly advantageous; which also makes me think of genetic algorithm simulations that show the evolution of rabbits dodging foxes or similar from a talk at the University of Sussex back in the day ...
Friday, November 25, 2011
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