Skill and billiards
- Computational pool is a relatively recent entrant into the group of games played by computer agents. It features a novel combination of properties that distinguish it from other such games, including continuous action and state spaces, uncertainty in execution, a unique turn-taking structure, and of course an adversarial nature. This combination leads to new challenges, both in modeling and reasoning about the game and in designing agents for effective play. We address the modeling challenges by presenting a model of generalized billiards games and showing that an equilibrium exists within this model. To address the practical challenges of designing an agent, we discuss CueCard, our agent which won the 2008 computational pool tournament, with a special focus on which new advancements made this agent successful. The second portion of the dissertation focuses on a topic inspired by the computational pool domain, that of execution skill. In many AI settings an agent is comprised of both action-planning and action-execution components. We first present experimental work in which we examine the relationship between the precision of the execution component, the intelligence of the planning component, and the overall success of the agent within our computational pool framework. Our motivation lies in determining whether higher execution skill rewards more strategic playing. Finally, we present a method for modeling imperfect execution skill in normal form games and examine the effect that changing execution skill levels can have in these games. We then study games in which players have imperfect execution skill and one player's true skill is not common knowledge. In these settings the possibility arises of a player "hustling", or pretending to have lower execution skill than they actually have. Focusing on repeated zero-sum games, we provide a hustle-proof strategy; this strategy guarantees a player the same payoff without knowledge of the opponents execution skill level as they could guarantee with knowledge of the opponent's true execution skill level.
|Type of resource
|electronic; electronic resource; remote
|1 online resource.
|Archibald, Christopher James
|Stanford University, Computer Science Department
|Statement of responsibility
|Christopher James Archibald.
|Submitted to the Department of Computer Science.
|Thesis (Ph.D.)--Stanford University, 2011.
- © 2011 by Christopher James Archibald
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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