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Department of Informatics Artificial Intelligence Lab (ARCHIVE)


A research program designed to elucidate intelligence, one of the oldest and most mysterious conundrums of mankind, must be able to cope with multiple temporal – short-term, life-time of individual (developmental) and evolutionary – as well as spatial scales (macroscopic, mesoscopic, and microscopic). The notion of embodiment, which has formed our major research target over the last 15 years, has dramatic implications for our understanding of intelligence. For example, behavior is not the result of brain processes only, but of a subtle interplay between brain, body (morphology and materials) and environment; an insight that contradicts the classical Cartesian position. According to this perspective, morphological and material characteristics of an organism can take over a large part of its functionality. The synthetic methodology – “understanding by building” – which has a long history (e.g. Richard Feynman, Nobel Prize in physics, once said “if I can’t build it, I don’t understand it”) constitutes our major approach, thereby marrying engineering and science, and because of our focus on embodiment, one of the major tools is robots (complemented by various others means). One last core assumption is the faith in Nature, the brilliance of evolutionary design. Bionics and biorobotics try to learn from Nature, which serves as an infinitely rich source of inspiration. In line with this philosophy we pursue a number of research directions that are all intended to contribute to our mission.

A lot of our research in the past has been on relatively low-level sensory-motor tasks such as locomotion (e.g. walking, running, jumping), navigation, and grasping. While this research is of interest in itself, in the context of artificial intelligence and cognitive science, this leads to the question of what these kinds of tasks have to do with higher levels of cognition, or to put it more provocatively, “What does walking have to do with thinking?”

This question is of course reminiscent of the notorious “symbol grounding problem”. In contrast to most of the research on symbol grounding, we propose to exploit the dynamic interaction between the embodied agent and the environment as the basis for grounding.

We use the term “morphological computation” to designate the fact that some of the control or computation can be taken over by the dynamic interaction derived from morphological properties (e.g. the passive forward swing of the leg in walking, the spring-like properties of the muscles, and the weight distribution). By taking morphological computation into account, an agent will be able to achieve not only faster, more robust, and more energy-efficient behavior, but also more situated exploration by the agent for the comprehensive understanding of the environment.

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