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Collaborating Authors

 University of Osnabrück


Sensorimotor Analogies in Learning Abstract Skills and Knowledge: Modeling Analogy-Supported Education in Mathematics and Physics

AAAI Conferences

In this summary report I give an account of research conducted over the last two years, showing the suitability and the advantages of applying computational analogy-engines in the analysis and design of analogy-based methods and tools in teaching and education. This overview constitutes the conclusion of the first phase of a multi-stage effort trying to introduce computational models of analogy also to education and the learning sciences, thus opening up these fields to computational tools and methods not only on an instrumental level, but also in analytical, conceptual, and design-oriented studies. I locate the "analogy-engines in the classroom" research program within the bigger schemes of studying human creativity and computational creativity, provide an introduction to the theoretical underpinnings of the endeavor, and revisit three worked out case studies serving as proofs of the feasibility of the overall approach.


Report on the Sixth Conference on Artificial General Intelligence

AI Magazine

Motivated by the original idea of artificial intelligence in the 1950s and 1960s, there has been a revival of research in general intelligence during the last years. The annual AGI conference series, which is the major event in this area, has been held in cooperation with AAAI since 2008. The sixth conference on AGI was held at Peking University, Beijing, from July 31 to August 3, 2013. AGI-13 was collocated with the International Joint Conference on Artificial Intelligence (IJCAI 2013), the major international AI conference. This was the first time an AGI conference took place in Asia.


An Ontology-based Multi-level Robot Architecture for Learning from Experiences

AAAI Conferences

One way to improve the robustness and flexibility of robot performance is to let the robot learn from its experiences. In this paper, we describe the architecture and knowledge-representation framework for a service robot being developed in the EU project RACE, and present examples illustrating how learning from experiences will be achieved. As a unique innovative feature, the framework combines memory records of low-level robot activities with ontology-based high-level semantic descriptions.