Abstract
“Boxology” is the graphical representation of patterns that are commonly observed in hybrid learning and reasoning systems. Since some hybrid systems also involve humans-in-the-loop, a need to identify patterns including humans is foreseen. With the help of use cases that involve humans-in-the-loop, this chapter provides a discussion on the typical roles performed by humans in hybrid systems and how they influence machine learning and/or knowledge engineering activities. As a result, it introduces a new element in boxology to represent a human and identify two abstract patterns for such human-in-the-loop scenarios.
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Notes
- 1.
Association for Advancement of Artificial Intelligence.
- 2.
- 3.
From now on “representation” instead of “engineering” is used because this is the terminology used by [6].
- 4.
While explaining the boxology patterns, we use the textual notations (ML), (KR) and (Human) to represent the knowledge processing components of the boxology and [data], [sym] to represent the input/output components.
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Witschel, H.F., Pande, C., Martin, A., Laurenzi, E., Hinkelmann, K. (2021). Visualization of Patterns for Hybrid Learning and Reasoning with Human Involvement. In: Dornberger, R. (eds) New Trends in Business Information Systems and Technology. Studies in Systems, Decision and Control, vol 294. Springer, Cham. https://doi.org/10.1007/978-3-030-48332-6_13
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