Online research in philosophy

Learning general concepts in imperfect environments is difficult since training instances often include noisy data, inconclusive data, incomplete data, unknown attributes, unknown attribute values and other barriers to effective learning. It is well known that people can learn effectively in imperfect environments, and can manage to process very large amounts of data. Imitating human learning behavior therefore provides a useful model for machine learning in real-world applications. This paper proposes a new, more effective way to represent imperfect training instances and (...) rules, and based on the new representation, a Human-Like Learning (HULL) algorithm for incrementally learning concepts well in imperfect training environments. Several examples are given to make the algorithm clearer. Finally, experimental results are presented that show the proposed learning algorithm works well in imperfect learning environments. (shrink)

Machine learning has been proven useful for solving the bottlenecks in building expert systems. Noise in the training instances will, however, confuse a learning mechanism. Two main steps are adopted here to solve this problem. The first step is to appropriately arrange the training order of the instances. It is well known from Psychology that different orders of presentation of the same set of training instances to a human may cause different learning results. This idea is used here for machine (...) learning and an order arrangement scheme is proposed. The second step is to modify a conventional noise-free learning algorithm, thus making it suitable for noisy environment. The generalized version space learning algorithm is then adopted to process the training instances for deriving good concepts. Finally, experiments on the Iris Flower problem show that the new scheme can produce a good training order, allowing the generalized version space algorithm to have a satisfactory learning result. (shrink)

The main purpose of this study is to explore and map the intellectual structure of business ethics studies during 1997–2006 by analyzing 85,000 cited references of 3,059 articles from three business ethics related journals in SSCI and SCI databases. In this article, co-citation analysis and social network analysis techniques are used to research intellectual structure of the business ethics literature. We are able to identify the important publications and the influential scholars as well as the correlations among these publications by (...) analyzing citation and co-citation. Three factors emerged in this study are: (1) ethical/unethical decision making, (2) corporate governance and firm performance, and (3) ethical principles and code of conduct. (shrink)

This study aims to propose a framework considering both economic issues and environmental effects in technology evaluation in order to provide firms’ decision makers a useful reference in adopting technologies that will enable them to fulfill corporate social responsibilities and get competitive advantages at the same time. Recently, the demands for technology evaluation have increased with the flourishing development of technology licensing, technology transaction or joint venture on the one hand and with the pressing needs of environmental protection for human (...) beings’ sustainable development on the other hand. Under such conditions, it thus goes without saying that firms’ decision makers are propelled to take into account both economic benefits and environmental effects in evaluating technologies by choosing low or nonpolluting technologies for manufacturing products. Although technology evaluation is not a new and emerging subject currently besetting scholars in the field of management, previous research on this topic has unwittingly left behind the pressing issue of environmental effects. Based on this observation, this study purports to develop a new framework for technology evaluation by taking both economic benefits and environmental perspectives into consideration. In it, we seek to demonstrate that our proposed framework will not only be a workable model but also can serve as a useful point of reference for technology appraisers and firms’ decision makers. (shrink)