Date of Award
9-2020
Document Type
Thesis
Degree Name
Master of Science
Department
Department of Electrical and Computer Engineering
First Advisor
Kenneth M. Hopkinson, PhD
Abstract
This research provides a heuristic algorithm for the detectives, who try to collectively capture a criminal known as Mr. X, in the Scotland Yard pursuer-evasion game. In Scotland Yard, a team of detectives attempts to converge on and capture a criminal known as Mr. X. The heuristic algorithm developed in this thesis is designed to emulate human strategies when playing the game. The algorithm uses the current state of the board at each time step, including the current positions of the detectives as well as the last known position of Mr. X. The heuristic algorithm then analyses all of the possible options. The heuristic algorithm then uses a process of elimination to detemine the best possible detective moves by running an appropriately constructed minimum cost flow maximum flow instance. The heuristic algorithm was tested in a series of experiments, in which the algorithm achieved a 57 win rate. This win rate was achieved using a random starting position for each of the pursuer detectives as well as for the evader, Mr. X. When Mr. X started at an easily accessible location, namely position 146, the pursuing detectives were able to capture him 62% of the time. These results show promise for this heuristic in pursuer-evader games like Scotland Yard.
AFIT Designator
AFIT-ENG-MS-20-S-003
DTIC Accession Number
AD1116459
Recommended Citation
Alamri, Arif M., "Artificial Intelligence in Pursuit-evasion Games, Specifically in the Scotland Yard Game" (2020). Theses and Dissertations. 4332.
https://scholar.afit.edu/etd/4332