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A General Model for Acquiring Knowledge
Abstract:In this paper, based on the work in , we further give a general model for acquiring knowledge, which first focuses on the research of how and when things involved in problems are made then describes the goals, the energy and the time to give an optimum model to decide how many related things are supposed to be involved in. Finally, we acquire knowledge from this model in which there are the attributes, actions and connections of the things involved at the time when they are born and the time in their life. This model not only improves AI theories, but also surely brings the effectiveness and accuracy for AI system because systems are given more knowledge when reasoning or computing is used to bring about results.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1075128Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 920
 Peng GuoQiang, "A framework for AI system", accepted by 2006 International Conference on AI.
 Peng GuoQiang and Cheng Hu, "A causal model for diagnostic reasoning", Journal of Computer Science and technology, Vol.15, No.3, May 2000.