Even More AI Topics on Serious Games

If the game involves a user programming agents and pitting them agains AI controlled agents, it is possible that some sort of pathfinding would need to be done as to allow the AI to reach the player in a believable manner. Implementing this topic would include things such as A*, Theta* and path smoothing.

Blackboard Architecture
This architecture seems to be really helpful when developing AI agents, as a platform that eases agent scalability and as a platform that enables inter-agent coordination, as well as dynamic logic changing with the addition and removal of Knowledge Sources. This topic would need to be further researched as there are already several blackboard architecture implementations out there for different kinds of problems.

State Machine For Non-Programmers Implementation
If the game involves teaching some sort of programmable agent, it should become apparent that we would need to implement some sort of state machine that is easy to use, easy to modify and fun to work with. This would probably lead to visual programming. Implementing this topic would include things such as abstraction/generalization of computer logic and the cognitive process of the player while engaging in visual programming.

In-Game Scripting Implementation
On the other hand, if we end up creating a game where the player would need to a more complex programming of the agent, a form of in-game scripting would be needed to facilitate this. This would have to be combined with other gameplay mechanics as to not make the game tedious in a 'create a solution, watch what happens, change the solution' cycle and make it more active and fun. The scripting language would have to be tailored to our game's needs.

This is something I didn't know about but can be quite useful. Capturing the actions of different gamers and then having the AI replicating those actions can create a believable experience, as the AI would learn the little quirks that human players have that are difficult to emulate in a computer controlled player. The implementation of this topic depends completely on the style and objective on the game that will be developed.

  • McGlinchey, Stephen (2004). Enabling Computers to Play Like Humans. In Ercim News 57(1),14-16
  • Nash, A. (2010). Theta*: Any-Angle Path Planning for Smoother Trajectories in Continuous Environments.
  • Rabin, Steve (2002) AI Game Programming Wisdom, United States, Charles River Media Inc.
  • Isla, Damian; Blumberg, Bruce (2002) Blackboard Architectures. In Steve Rabin (Ed.) In AIGame Programign Wisdom (pp 333-344) United States, Charles River Media Inc.

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