In this paper, we study the asset pricing implication of imprecise knowledge about rare events. Modeling rare events as jumps in the aggregate endowment, we explicitly solve the equilibrium asset prices in a pure-exchange economy with a representative agent who…

This paper presents a knowledge-based approach for capturing data and rationale, so
that the experience and insights gained while pursuing a major project or endeavor can
be utilized when pursuing future endeavors of a similar nature. The proposed

Complex goods and processes require ever more sophisticated and specialized knowledge; harnessing multiple kinds of expertise to execute tasks, solve problems, and develop strategies is increasingly critical to organizations' survival. When specialists come together, however, they often speak in different…

An increasing number of organizations are involved in the development of strategic
information systems for effective linkages with their suppliers, customers, and other
channel partners involved in transportation, distribution, warehousing and maintenance
activities. An efficient inter-organizational inventory…

Learning from experience, the cyclical interplay of thinking and doing, is increasingly
important as organizations struggle to cope with rapidly changing environments and more
complex and interdependent sets of knowledge. This paper confronts two central issues
for organizational learning: (1)…

Knowledge acquisition for systems based on knowledge can be called knowledge engineering, according to Feigenbaum (1980) who used the term to describe the reduction of a wide context of knowledge for a set of facts and rules. The term Knowledge…

Seroepidemiological studies have demonstrated that the presence of the tapeworm carrier in the household or in the close environment is the main risk factor associated to human and swine cysticercosis. Intervention measures evaluated are: 1) Mass treatment against the adult…

Most neural network learning algorithms cannot use knowledge other than what is provided in the training data. Initialized using random weights, they cannot use prior knowledge such as knowledge stored in previously trained networks. This manuscript thesis addresses this problem.…

Inspirée par les débats portant sur la typologie de la recherche proposée par Michael Burawoy (2005b) et fondée sur une analyse qualitative de vingt-cinq entrevues auprès de professeurs en histoire, en économie et en sociologie, notre investigation a comme but…

In the restricted single-machine common due date problem the goal is to find a schedule for the n jobs which jointly minimizes the sum of earliness and tardiness penalties, while for the weighted tardiness problem the goal is to find…