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Mechanical Cognitivization

Authors:
Gideon Avigad
Avi Weiss

Keywords: cognitive robotics; developmental robotics; evolutionary algorithms.

Abstract:
The common approach for training robots is to expose them to different environmental scenarios, training their controllers to have the best possible commands when untrained scenarios are encountered. When humans train, they do the same. They try new manipulations by performing within different environments. However, humans training (and in fact development from infancy to maturity) also includes a type of training which, although claimed to improve cognitive capabilities, has not, to date, been adopted for the training of robots. This type of training involves the restriction of manipulation capabilities while performing different tasks, e.g., climbing with just one hand. The hereby reported upon research aims at exploring the invigorating idea that such training would enhance the robustness of robots and moreover may increase our understanding of why humans utilize such training in the first place. The main idea has been patented and is here published by a new name: Mechanical Cognitivization (MC).

Pages: 116 to 119

Copyright: Copyright (c) IARIA, 2014

Publication date: May 25, 2014

Published in: conference

ISSN: 2308-4197

ISBN: 978-1-61208-340-7

Location: Venice, Italy

Dates: from May 25, 2014 to May 29, 2014