Abstract
In this paper, we take a look back at the problem of creating an intelligent billiard player on a computer simulated table by using optimization techniques. We setup the problem by first defining the equations that describe the ball movements on a pool table, and go on to create a function that will be minimised to give us a player with the ability to reposition itself almost anywhere on a given table. We then look at possible strategies that the player can use to play intelligently while at the same time only looking one shot in advance. Pre-computed tables are introduced in the context of finding good starting points for the optimization model, thus reducing execution time and allowing the possibility of looking more than one shot ahead.
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This research was partially supported by NSERC grant OGP0005491.
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Landry, JF., Dussault, JP. AI Optimization of a Billiard Player. J Intell Robot Syst 50, 399–417 (2007). https://doi.org/10.1007/s10846-007-9172-7
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DOI: https://doi.org/10.1007/s10846-007-9172-7