Site Search
Computer Science

Photos

Dr. Robert KentDr. Robert Kent
Dr. Robert Kent
Xiaobu Yuan, Ph.D.Dr. Xiaobu Yuan
Dr. Xiaobu Yuan
Windsor WaterfrontWindsor Waterfront Park
Windsor Waterfront Park
Imran Ahmad, Ph.D.Dr. Imran Ahmad
Dr. Imran Ahmad
Jessica Chen, Ph.D.Dr. Jessica Chen
Dr. Jessica Chen
Dr. Ziad Kobti lecturingDr. Ziad Kobti
Dr. Ziad Kobti
Robin Gras, Ph.D.Dr. Robin Gras
Dr. Robin Gras
Dr. Luis RuedaDr. Luis Rueda
Dr. Luis Rueda
Arunita Jaekel, Ph.D.Dr. Arunita Jaekel
Dr. Arunita Jaekel
Christie Ezeife, Ph.D.Dr. Christie Ezeife
Dr. Christie Ezeife
Lambton TowerLambton Tower
Lambton Tower
Dr. Scott GoodwinDr. Scott Goodwin
Dr. Scott Goodwin
Alioune Ngom, Ph.D.Dr. Alioune Ngom
Dr. Alioune Ngom

Multi-Objective Pathfinding in Dynamic Environments

Add this event into your calendar using the iCAL format
  • Mon, 06/12/2017 - 10:30am - 12:00pm




Multi-Objective Pathfinding in Dynamic Environments

MSc Thesis Proposal by:

Halen Whiston

Date:  Monday, June 12th, 2017
Time:  10: 30 am – 12:00 pm
Location: 3105, Lambton Tower

Abstract: Traditional pathfinding solutions focus on determining a shortest path between any given two points on a graph. While these solutions are suitable for routing and exploration problems, they become insufficient when the probability of losing valuable resources (risk) along those computed paths is too great. Strategic pathfinding solutions that attempt to prioritize resources over path length may not be the most optimal either, as forfeiting a shorter route could prove to be detrimental in the long term depending on the situation. As such, the optimal path becomes dependent on both the agent’s objective and its urgency to reach (or maintain) that same objective. This research’s aim is to determine a compromise between traditional pathfinding solutions and strategic pathfinding solutions that can be applicable to both types of scenarios. Our work will include a thorough analysis and comparison of successful traditional pathfinding solutions (such as Dijkstra’s Algorithm and A* Search), and related strategic pathfinding solutions (Holder’s Strategic Pathfinding Solution). These solutions will be pitted against one another using map data borrowed from BioWare-developed Dragon Age: Origins. Due to the nature of the problem, the map data will need to be refined in order to accommodate elements from both traditional and strategic pathfinding scenarios. Our experiments will be evaluated by comparing efficiencies of previous solutions and the proposed solution at a base level.

Thesis Committee:
Internal Reader: Dr. Arunita Jaekel
External Reader: Dr. Myron Hlynka
Advisor: Dr. Scott Goodwin



csgradinfo@uwindsor.ca
(519)253-3000


See More: