Name
Title | ||
|---|---|---|
Evaluating Morphological Computation in Muscle and DC-motor Driven Models of Human Hopping |
Abstract | ||
|---|---|---|
In the context of embodied artificial intelligence, morphological computation refers to processes, which are conducted by the body (and environment) that otherwise would have to be performed by the brain. Exploiting environmental and morphological properties are an important feature of embodied systems. The main reason is that it allows to significantly reduce the controller complexity. An important aspect of morphological computation is that it cannot be assigned to an embodied system per se, but that it is, as we show, behavior and state dependent. In this work, we evaluate two different measures of morphological computation that can be applied in robotic systems and in computer simulations of biological movement. As an example, these measures were evaluated on muscle and DC-motor driven hopping models. We show that a state-dependent analysis of the hopping behaviors provides additional insights that cannot be gained from the averaged measures alone. This work includes algorithms and computer code for the measures. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.3389/frobt.2016.00042 | FRONTIERS IN ROBOTICS AND AI |
Keywords | Field | DocType |
morphological computation,sensorimotor loop,embodied artificial intelligence,muscle models,information theory | Information theory,Robotic systems,Control theory,Computer science,Source code,Simulation,DC motor,Embodied cognition,Artificial intelligence,Biological movement,Machine learning,Computation | Journal |
Volume | ISSN | Citations |
3.0 | 2296-9144 | 5 |
PageRank | References | Authors |
0.47 | 12 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Keyan Ghazi-Zahedi | 1 | 18 | 3.51 |
| Daniel F. B. Haeufle | 2 | 7 | 3.56 |
| Guido Montufar | 3 | 7 | 5.63 |
| Syn Schmitt | 4 | 13 | 6.01 |
| Nihat Ay | 5 | 10 | 1.97 |