Practical Development of Goal-Oriented Action Planning AI
By: David Pittman
Supervisor: Jeff Wofford
Masters of Interactive Technology degree conferred March 23, 2007
Thesis / Project completed: March 21, 2007

As real-time graphics continue to approach realism and gameplay systems become increasingly complex, game AI must progress in parallel to maintain the illusion of believable characters. The decision-making architecture known as Goal-Oriented Action Planning (GOAP) offers dynamic problem solving, which is a key ingredient in crafting AIs which appear to understand their environment and react in a logical manner. This project analyzes the development of a GOAP-based AI and its application to various game genres, with consideration to the practicality of the technology. In this context, practical is defined as being able to be implemented in an interpreted scripting language at production quality in a reasonable amount of time, performing efficiently, and producing equal or better results compared to traditional AI techniques. In the context of certain game genres such as tactical shooters and strategy games, coordinated character behavior is as important as individual behavior to the success of an AI system. Prior implementations of GOAP have used informal solutions to the problem of coordinated decision-making. This project proposes a scheme for implementing command and control hierarchies which use GOAP at every level to propagate orders from a commanding unit to atomic AI agents.

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