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Titlebook: Artificial Intelligence in Economics and Managment; An Edited Proceeding Phillip Ein-Dor Conference proceedings 1996 Kluwer Academic Publis

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樓主: vein220
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發(fā)表于 2025-3-25 06:58:17 | 只看該作者
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發(fā)表于 2025-3-25 11:19:12 | 只看該作者
23#
發(fā)表于 2025-3-25 13:17:05 | 只看該作者
https://doi.org/10.1007/978-3-663-10044-7ese models are inductively found by a limited incremental search based on the current model and by combinations of past models from a space restricted by the imposition of a priori beliefs. The action of the agent is then decided by a search of the goal space where it intersects the model space (if any).
24#
發(fā)表于 2025-3-25 17:38:45 | 只看該作者
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發(fā)表于 2025-3-25 21:20:21 | 只看該作者
26#
發(fā)表于 2025-3-26 00:43:21 | 只看該作者
The Effect of Training Data Set Size and the Complexity of the Separation Function on Neural Networkssifying among consumer types, rating of firms’ bonds, etc. Neural networks are recognized as important and emerging methodologies in the area of classification. In this paper, we study the effect of training sample size and the neural network topology on the classification capability of neural netw
27#
發(fā)表于 2025-3-26 04:19:17 | 只看該作者
Imaginal Agents. Image Theory, a well-established framework for analyzing and understanding the activities of decision-makers (DM), is applied to provide conceptual guidelines for establishing inter-agent communication; independent agent deliberation, and the evolution or modification of individual agent behavior.
28#
發(fā)表于 2025-3-26 08:47:53 | 只看該作者
Financial Product Representation and Development Using a Rule-Based Systemcustomers in shorter time. As a consequence it is necessary to develop suitable information systems that support the process of product development and product management. More complex products may be built from simpler basic products. In this paper a general methodology for the abstract representat
29#
發(fā)表于 2025-3-26 15:11:58 | 只看該作者
Applications of Artificial Intelligence and Cognitive Science Techniques in Bankingl be decision support systems and knowledge-based decision support systems. Thus we have to consider the knowledge acquisition stage which is known as the bottleneck in the construction of these systems. We will present a model for learning strategies established by a decision maker for a feature ta
30#
發(fā)表于 2025-3-26 20:42:23 | 只看該作者
AI-Supported Quality Function Deploymention, Artificial Intelligence (AI) tools can further enhance the functionality of QFD tools. A graph-based information representation is proposed as the basis for integrating various QFD and AI tools. An architecture of a computation QFD (CQFD) tool based on the graph-based modeling environment .-dim
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