Machine Learning in Artificial Intelligence: Towards a Common Understanding
This work provides terminological clarity for researchers and practitioners in AI and related fields, though it is incremental as it builds on existing literature.
The paper tackles the problem of inconsistent usage of the terms 'machine learning' and 'artificial intelligence' by reviewing literature and presenting a conceptual framework to clarify their relationship and the role of machine learning in building intelligent agents.
The application of "machine learning" and "artificial intelligence" has become popular within the last decade. Both terms are frequently used in science and media, sometimes interchangeably, sometimes with different meanings. In this work, we aim to clarify the relationship between these terms and, in particular, to specify the contribution of machine learning to artificial intelligence. We review relevant literature and present a conceptual framework which clarifies the role of machine learning to build (artificial) intelligent agents. Hence, we seek to provide more terminological clarity and a starting point for (interdisciplinary) discussions and future research.