The discovery of risks and opportunities, known collectively as chances, can have a significant impact on decision making. Chances (risks or opportunities) can be discovered from our daily observations and background knowledge. A person can easily identify chances in a news article. In doing so, the person combines the new information in the article with some background knowledge. Hence, we develop a deductive system to discover relative chances with respect to a particular chance seeker. A chance discovery system that uses a general purpose knowledge base and specialized reasoning algorithms is proposed. The thesis evaluates the implementation of this chance discovery system and discusses the achievements and limitations of its elements, such as Natural Language Processing Tool, Knowledge Entry Tool, Inference Engine and Planner. Finally, A case study about a virtual transportation planning domain implemented using SHOP planner is presented. Example chances are detected in this domain. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .W89. Source: Masters Abstracts International, Volume: 44-03, page: 1418. Thesis (M.Sc.)--University of Windsor (Canada), 2005
