By Yoshitake Akiyama, Kikuo Iwabuchi, Keisuke Morishima (auth.), Nathan F. Lepora, Anna Mura, Holger G. Krapp, Paul F. M. J. Verschure, Tony J. Prescott (eds.)
This publication constitutes the refereed court cases of the second one overseas convention on Biomimetic and Biohybrid platforms, dwelling Machines 2013, held in London, united kingdom, in July/August 2013. The sixty five revised complete papers awarded have been conscientiously reviewed and chosen from a variety of submissions. The papers are specified on the intersection of study on novel live-like applied sciences encouraged via medical research of organic platforms, biomimetics, and study that seeks to interface organic and synthetic structures to create biohybrid systems
Read or Download Biomimetic and Biohybrid Systems: Second International Conference, Living Machines 2013, London, UK, July 29 – August 2, 2013. Proceedings PDF
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Additional info for Biomimetic and Biohybrid Systems: Second International Conference, Living Machines 2013, London, UK, July 29 – August 2, 2013. Proceedings
Then, we recorded a dataset of 200 pairs of visual position ground true movement that we used to test the network. The error of the network was calculated as Euclidean distance between the ground truth movement and the output of the network. 071◦. 6 Conclusions In this work, we have presented a new bio-inspired algorithm to speeds-up the learning of saccade control. This control requires to learn the transformation that converts the visual location of the target into a gaze direction. The environment surrounding the agent provides several visual stimuli, so that the robot can choose to explore the one with higher uncertainty.
This is contrasted with sensory substitution, where the sensory experience provided by the device is reducible to an existing modality . As a sensory augmentation device is not designed to merely translate a scene, different patterns of activity can be used to communicate different types of information from moment to moment, allowing for greater functional flexibility compared to sensory substitution devices. In sensory augmentation, the aim is to reproduce the function of a sensory modality as a way of interacting with the world, rather than translate the form of one modality into the form of another .
Evolution of the learning process with diﬀerent decision making strategies the target randomly, the target with the higher variance and the one with the lower variance. Choosing the feature with a bigger variance allows the system to explore the region with higher uncertainty and, as expected, it converges faster than the other methods. Choosing the feature with the lower variance forces the system to explore already known regions, so that it does not converge and it represents the worst case. The performance of the random choice is in between the other two.