Abstract
Most agents in computer games are designed using classical symbolic artificial intelligence (AI) techniques. The AI techniques include production rules for very large branching and conditional statements, as well as search techniques, including branch-and-bound, heuristic search, and A* (Russel & Norvig, 2003). Planning techniques, such as STRIPS (Stanford Research Institute Problem Solver) (Fikes & Nilsson, 1971) and hierarchical task network (HTN) (Erol, 1996) planning are common. Also, situational case-based reasoning, finite-state machines, classical expert systems, Bayesian networks, and other forms of logic, including predicate calculus and its derivatives, such as description logics (Baader et al., 2003), form the foundation of many game agents that leverage AI techniques. The game agents are typically created with
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