Christopher Archibald

Computational Pool: A New Challenge for Game Theory Pragmatics

Computational pool is a relatively recent entrant into the group of games played by computer agents. It features a unique combination of properties that distinguish it from oth- ers such games, including continuous action and state spaces, uncertainty in execution, a unique turn-taking structure, and of course an adversarial nature. This article discusses some of the work done to date, focusing on the software side of the pool-playing problem. We discuss in some depth CueCard, the program that won the 2008 computational pool tournament. Research questions and ideas spawned by work on this problem are also discussed. We close by announcing the 2011 computational pool tournament, which will take place in conjunction with the Twenty-Fifth AAAI Conference.

A simple approach to a vision-guided unmanned vehicle

This paper describes the design and implementation of a vision-guided autonomous vehicle that represented BYU in the 2005 Intelligent Ground Vehicle Competition (IGVC), in which autonomous vehicles navigate a course marked with white lines while avoiding obstacles consisting of orange construction barrels, white buckets and potholes. Our project began in the context of a senior capstone course in which multi-disciplinary teams of five students were responsible for the design, construction, and programming of their own robots. Each team received a computer motherboard, a camera, and a small budget for the purchase of additional hardware, including a chassis and motors. The resource constraints resulted in a simple vision-based design that processes the sequence of images from the single camera to determine motor controls. Color segmentation separates white and orange from each image, and then the segmented image is examined using a 10x10 grid system, effectively creating a low resolution picture for each of the two colors. Depending on its position, each filled grid square influences the selection of an appropriate turn magnitude. Motor commands determined from the white and orange images are then combined to yield the final motion command for video frame. We describe the complete algorithm and the robot hardware and we present results that show the overall effectiveness of our control approach.

Hustling in repeated zero-sum games with imperfect execution

We study repeated games in which players have imperfect execution skill and one players 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 maximizes a players payoff, regardless of the true skill level of the other player.

A Distributed Agent for Computational Pool

Games with continuous state and action spaces present unique challenges from an artificial intelligence (AI) viewpoint. Billiards, or pool, is one such domain that has been the focus of several research efforts aimed at designing AI agents to play successfully. Due to the continuous nature of the actions, it is natural to believe that the more time an agent has to investigate actions, the better it will perform. This paper gives a thorough description of a successful agent with a novel distributed architecture, designed for being able to grant further time for shot simulation and analysis through the utilization of many CPUs. A brief analysis of the distributed component of the agent is presented, as well as how much the extra time thus obtained contributed to its success, especially when compared to its other novel components. The described agent, CueCard, won the Computer Olympiad computational pool tournament held in 2008.

Measuring conflict in a multi-source environment as a normal measure

In a multi-source environment, each source has its own credibility. If there is no external knowledge about credibility then we can use the information provided by the sources to assess their credibility. In this paper, we propose a way to measure conflict in a multi-source environment as a normal measure. We examine our algorithm using three simulated examples of increasing conflict and one experimental example. The results demonstrate that the proposed measure can represent conflict in a meaningful way similar to what a human might expect and from it we can identify conflict within our sources.

Enhancement of thermal imagery using a low-cost high-resolution visual spectrum camera for scene understanding

Thermal-infrared cameras are used for signal/image processing and computer vision in numerous military and civilian applications. However, the cost of high quality (e.g., low noise, accurate temperature measurement, etc.) and high resolution thermal sensors is often a limiting factor. On the other hand, high resolution visual spectrum cameras are readily available and typically inexpensive. Herein, we outline a way to upsample thermal imagery with respect to a high resolution visual spectrum camera using Markov random field theory. This paper also explores the tradeoffs and impact of upsampling, both qualitatively and quantitatively. Our preliminary results demonstrate the successful use of this approach for human detection and accurate propagation of thermal measurements in an image for more general tasks like scene understanding. A tradeoff analysis of the cost-to-performance as the resolution of the thermal camera decreases is provided.