NEW HUMAN-MACHINE RELATIONS REQUEST A NEW PARADIGM: UNDERSTANDING ARTIFICIAL INTELLIGENCE.
In: Economic & Social Development: Book of Proceedings; 2019, p451-458, 8p; (2019-05-01) S. 451-458
Online
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Zugriff:
We make decisions based on our aspirations. We don't choose between experiences; we choose between memories of experiences. And even when we think about the future, we don't think of our future normally as experiences. We think of our future as anticipated memories. And basically, you can look at this, you know, as a tyranny of the remembering self, and you can think of the remembering self-sort of dragging the experiencing self through experiences that the experiencing self doesn't need. This paper demonstrates how to build a knowledge-base which contains a decision-maker's aspiration. Our environment, the context of the decision, can only affect what is stored in our long-term memory (LTM). We retrieve what is in our LTM through the working memory (WM). Organizing our aspirations can be supported by an artificial intelligence (AI) algorithm. We developed a Knowledge-based System shell, namely Doctus KBS. It can generate a Case-Based Graph classifying the cases acquired from the domain expert. This Graph does not show dependencies, but the if-then rules induced by processing the cases. The if-then rules may be read from the root of the graph towards its leaves, where the value of the outcome is shown. The storing of experience in knowledge-bases and the discernment of the if-then rules serve the necessary sharing of knowledge. It would be useful if the recognition of thinking patterns and the if-then rules between aspirations were included in smart tools. The great benefit of the Case-Based Rule Reasoning is the reduced size, i.e. the significantly decreased number of the attributes. In the old paradigm it is a question of what AI can still know. The new paradigm could be the question of how working memory could make up deficiencies. [ABSTRACT FROM AUTHOR]
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Titel: |
NEW HUMAN-MACHINE RELATIONS REQUEST A NEW PARADIGM: UNDERSTANDING ARTIFICIAL INTELLIGENCE.
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Autor/in / Beteiligte Person: | Velencei, Jolan |
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Quelle: | Economic & Social Development: Book of Proceedings; 2019, p451-458, 8p; (2019-05-01) S. 451-458 |
Veröffentlichung: | 2019 |
Medientyp: | Konferenz |
ISSN: | 1849-7535 (print) |
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