A Perceptual Memory System for Affordance Learning in Humanoid Robots
- Cite this paper as:
- Kammer M., Tscherepanow M., Schack T., Nagai Y. (2011) A Perceptual Memory System for Affordance Learning in Humanoid Robots. In: Honkela T., Duch W., Girolami M., Kaski S. (eds) Artificial Neural Networks and Machine Learning – ICANN 2011. ICANN 2011. Lecture Notes in Computer Science, vol 6792. Springer, Berlin, Heidelberg
Memory constitutes an essential cognitive capability of humans and animals. It allows them to act in very complex, non-stationary environments. In this paper, we propose a perceptual memory system, which is intended to be applied on a humanoid robot learning affordances. According to the properties of biological memory systems, it has been designed in such a way as to enable life-long learning without catastrophic forgetting. Based on clustering sensory information, a symbolic representation is derived automatically. In contrast to alternative approaches, our memory system does not rely on pre-trained models and works completely unsupervised.
KeywordsCognitive robotics artificial memory life-long learning affordances
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