Modeling Adaptive Learning Agents for Domain Knowledge Transfer

The implementation of intelligent agents in industrial applications is often prevented by the high cost of adopting such a system to a particular problem domain. This paper states the thesis that when learning agents are applied to work environments that require domain-specific experience, the agent...

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Veröffentlicht in:	2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C) S. 660 - 665
1. Verfasser:	Hoser, Moritz
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.09.2019
Schlagworte:	Adaptation models Adaptive learning Adaptive Learning Agents Costs Domain modeling Intelligent agents Knowledge based systems Knowledge engineering Knowledge transfer Manuals Metamodeling Model driven engineering Multi-modeling
Online-Zugang:	Volltext
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