Visual Data Mining of Player Traces in Interactive Environments -- Heuristic search methods for pathfinding -- Pattern-based AI Scripting -- Case-Based Reasoning and User-Generated Gameplay -- Knowledge acquisition for adaptive game AI -- Game AI as Storytelling -- Affective Interactive Narrative -- Virtual Humans -- Interactive Drama -- Dynamic Behaviour Trees.

Techniques used for Artificial Intelligence (AI) in commercial video games are still far from state-of-the art in Academia, but with graphics in video games coming close to photo realistic quality, and multi-processor architectures getting common in console and PC game platforms, sophisticated AI is getting into the focus of the video game industry as the next big thing for enhancing the player experience. "Artificial Intelligence for Games" collects some of the most relevant results from Academia in the area of Artificial Intelligence for games. The selection of contributions has been biased towards rigorous and theoretically grounded work that is also supported with developed prototypes, which should pave the way for the integration of academic AI techniques into state-of-the-art electronic entertainment games. The chapters in the book cover different areas relevant to AI in commercial games: Real-time heuristic search algorithms that alleviate the scalability problem of A* techniques Authoring tools that facilitate the construction by game designers (typically non-programmers) of behavior controlling software Algorithms for automatically or semi-automatically learning complex behavior from recorded traces of human players Techniques that try to deliver the best possible experience by dynamically adapting the game to the player interaction "Artificial Intelligence for Games " is a must-read for researchers and practicing engineers in the game industry. Key results from applied research on AI within the last 10 years have been collected here to provide a reference work for both Academia and Industry that will help to close the gap between both worlds.