This thesis presents an approach to generating intelligent behaviour for agents in computer game-like worlds. Designing and implementing such agents is a difficult task because they are required to act in real-time and respond immediately to unpredictable changes in their environment. Such requirements have traditionally caused problems for AI techniques. To enable agents to generate intelligent behaviour in real-time, complex worlds, research has been carried out into two areas of agent construction. The first of these areas is the method used by the agent to plan future behaviour. To allow an agent to make efficient use of its processing time, a planner is presented that behaves as an anytime algorithm. This anytime planner is a hierarchical task network planner which allows a planning agent to interrupt its planning process at any time and trade-off planning time against plan quality. The second area of agent construction that has been researched is the design of agent architectures. This has resulted in an agent architecture with the functionality to support an anytime planner in a dynamic, complex world. A proof-of-concept implementation of this design is presented which plays Unreal Tournament and displays behaviour that varies intelligently as it is placed under pressure
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