Integrated learning architectures
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Research in systems where learning is integrated to other components like problem solving, vision, or natural language is becoming an important topic for Machine Learning. Situations where learning methods are embedded or integrated into broader systems offers new theoretical challenges to ML and enlarge the potential range of ML applications. In this position paper we propose the research topic of integrated learning architectures as an initial discussion of the role of learning in intelligent systems. We review the current state of the art and characterise several dimensions along which integrated learning architectures may vary. This paper has been prepared as a position paper with the purpose of providing an initial common ground for discussion in the ECML-93 Workshop on Integrated Learning Architectures. The paper has been edited by E Plaza on the basis of the individual contributions of the authors.
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- Integrated learning architectures
- Book Title
- Machine Learning: ECML-93
- Book Subtitle
- European Conference on Machine Learning Vienna, Austria, April 5–7, 1993 Proceedings
- pp 427-441
- Print ISBN
- Online ISBN
- Series Title
- Lecture Notes in Computer Science
- Series Volume
- Series Subtitle
- Lecture Notes in Artificial Intelligence
- Series ISSN
- Springer Berlin Heidelberg
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- Author Affiliations
- 1. Institut d'Investigació en Intel-ligència Artificial (CEAB-CSIC), Camí de Santa Bàrbara, 17300, Blanes, Catalunya, Spain
- 2. University of Throndheim, Norway
- 3. Georgia Institute of Technology, USA
- 4. AI-Lab, Vrije Universiteit Brussels, Belgium
- 5. Universiteit van Amsterdam, Netherlands
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