{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/evaluating-morphological-computation-in","title":"Evaluating Morphological Computation in Muscle and DC-motor Driven Models of Human Hopping","arxiv_id":"1512.00250","date":"2015-12-01","proceeding":null,"authors":["Keyan Ghazi-Zahedi","Daniel F. B. Haeufle","Guido Montufar","Syn Schmitt","Nihat Ay"],"abstract":"In the context of embodied artificial intelligence, morphological computation\nrefers to processes which are conducted by the body (and environment) that\notherwise would have to be performed by the brain. Exploiting environmental and\nmorphological properties is an important feature of embodied systems. The main\nreason is that it allows to significantly reduce the controller complexity. An\nimportant aspect of morphological computation is that it cannot be assigned to\nan embodied system per se, but that it is, as we show, behavior- and\nstate-dependent. In this work, we evaluate two different measures of\nmorphological computation that can be applied in robotic systems and in\ncomputer simulations of biological movement. As an example, these measures were\nevaluated on muscle and DC-motor driven hopping models. We show that a\nstate-dependent analysis of the hopping behaviors provides additional insights\nthat cannot be gained from the averaged measures alone. This work includes\nalgorithms and computer code for the measures.","url_abs":"http://arxiv.org/abs/1512.00250v3","url_pdf":"http://arxiv.org/pdf/1512.00250v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"evaluating-morphological-computation-in","repo_url":"https://github.com/kzahedi/MC","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"evaluating-morphological-computation-in","repo_url":"https://github.com/kzahedi/entropy","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}