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You're tasked with implementing a computer player for a real-time strategy (RTS) game. Assuming that there is no fog-of-war, how do you implement a system to allow the computer player to determine what parts of the map are controlled by enemy players, and which parts are open to easy exploitation? How do you identify the choke points on the map? How do you find the boundary between the parts of the map under your control and the parts of the map controlled by enemy players? How do you detect an impending enemy attack or a change in an enemy's offensive posture?
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How can you determine if a ray intersects a sphere? The more efficient your solution, the better.
What are some of the limitations of state machines? When is the use of state machines appropriate, and when are they insufficient to generate the kinds of behaviors you need in a game?
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What is planning? How is it used, and what are its advantages? Is it feasible to use planning in real-time games? If so, name any titles where planning has been used for any part of the AI. Describe the architecture of a planning-based AI system for any genre of game.
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Imagine you have to write a Tic-Tac-Toe game in which a human player plays against the computer. Discuss the different ways in which you could implement the computer’s artificial intelligence for the game. Which method would you ultimately choose? And why?
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You're in charge of implementing a stealth game similar to Thief: The Dark Project, and you need guards in your game that have imperfect vision and hearing and inhabit dimly-lit castles, and they can search the area for the player if they think there's an intruder around. How do you model the sensory systems of these guards, and how do you aggregate auditory, visual, and other kinds of stimuli in this system? How do you implement the various alert states for the guards, and why?
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