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Performance Evaluation of Pathfinding Algorithm

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  • Fri, 09/14/2018 - 1:00pm - 3:00pm

Performance Evaluation of Pathfinding Algorithm

MSc Thesis Proposal by:

Harinder Kaur Sidhu

Date:  Friday, September 14th, 2018
Time:  1: 00 pm – 3:00 pm
Location: 3105, Lambton Tower

Abstract:  Pathfinding is the search for an optimal path from a start location to a goal location in a given environment. In Artificial Intelligence pathfinding algorithms are typically designed as a kind of graph search. These algorithms are applicable in a wide variety of applications such as computer games, robotics, networks, and navigation systems. The performance of these algorithms is affected by several factors such as the problem size, path length, the number and distribution of obstacles, data structures and heuristics. When new pathfinding algorithms are proposed in the literature, their performance is often investigated empirically (if at all). Proper experimental design and analysis is crucial to provide an informative and non-misleading evaluation. In this research, we survey many papers and classify them according to their methodology, experimental design, and analytical techniques. We identify some weaknesses in these areas that are all too frequently found in reported approaches. We then provide a set of guidelines for the experimenter and examine case studies that demonstrate the pitfalls in deviating from best practices.

Thesis Committee:
Internal Reader: Dr. Arunita Jaekal
External Reader: Dr. Christina Semenuik
Advisor: Dr. Scott Goodwin

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