About

Remote Shepherd is the capstone project for Long Shot Games, a group of five graduate students in RIT's Game Design and Development masters program. The game allows the player to step into the shoes of a group of vigilantes who have decided to put their skills gained as Marine Scout Snipers to use in cleaning their city of criminal organizations. This blog will track both the ongoing design and development of the project.

Monday, January 10, 2011

AI Prototype

One of these dots is feared by the rest

The AI Flash prototype is quickly starting to function more like what we want in the game. In this latest iteration we have three features being demonstrated: fleeing, contagious fear and behaviors. Clicking on an empty space in the world simulates a gunshot in the real game, creating fear in nearby agents. The frightened agents flee towards safeplaces (SP). As they run past non-frightened agents they transfer a little fear to them. One frightened person running past another won't cause the other to run, but many frightened people running past them will. In this system a well placed shot can even cause a panic as the fear continues to spread.

The red encircled dots are frightened and
running to a safeplace


The other aspect of our AI system that is being demonstrated (though harder to capture in screen shots) is the behaviors. Basing the agents behaviors on our planned first mission, one of the agents is a debt collector, and the rest of the agents are debtors. The debt collector wanders around the world space, while the debtors try to avoid the collector while also wandering randomly between the waypoints (W). Identifying the debt collector involves exactly the kind of process we are hoping to elicit in the actual game: the player must observe the world and look for disruptions in a pattern, in this case look for agents who seem to be having their normal path to a waypoint disturbed; the collector is likely to be near them.

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