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.

Sunday, March 20, 2011

Not The Man I Used To Be

As you know, Remote Shepherd has had a reboot of sorts. What this means for AI is essentially starting over on character design. Previously we had five types of AI planned for the first level (the Market Mission): three different kinds of shopkeepers who would resist the debt collector to varying degrees, regular people just out shopping, and the debt collector himself. While all the designs for the AI characters were finished I had fortunately only implemented the shopper in code.

Behavior trees and finite state engines for the original AI characters

In addition to the problems Eric mentioned in his post, the original design of the second and third missions was incredibly vague in terms of AI and behaviors, and trying to come up with AI to fit the environment and narrative wasn't working ("So what'll be the NPCs be doing in Mission 2?" "Uhhh"). With the new park environment we have a much larger pool of behaviors that people might engage in in that space, and the hard part became trimming the list to behaviors that served our gameplay purpose: to act as a red herring. This trimming is just a prioritization though, not a deletion of any behaviors. The game will also need AI characters that are not red herrings, but are there to flesh out the environment and make it seem realistic and alive. The three characters (in addition to the unique target characters) that we have prioritized are: The Reader, The Walker, and The Jogger.

Sample of behavior trees and finite state engines for The Reader, The Jogger, The MobGuy and The BodyGuard

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