Imitation Learning in Robots
Imitation is the ability to recognize and reproduce others’ actions – By extension, imitation learning is a means of learning and developing new skills from observing these skills performed by another agent. Imitation learning (IL) as applied to robots is a technique to reduce the complexity of search spaces for learning. When observing either good or bad examples, one can reduce the search for a possible solution, by either starting the search from the observed good solution (local optima), or conversely, by eliminating from the search space what is known as a bad solution. Imitation learning offers an implicit means of training a machine, such that explicit and tedious programming of a task by a human user can be minimized or eliminated. Imitation learning is thus a “natural” means of training a machine, meant to be accessible to lay people.
- Billard, A., Calinon, S., Dillmann, R., & Schaal, S. (2008). Robot programming by demonstration. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics. Cambridge, MA: MIT Press.Google Scholar
- Nehaniv, C. L., Ab, H. A., & Dautenhahn, K. (1999). Of hummingbirds and helicopters: An algebraic framework for interdisciplinary studies of imitation and its applications. In J. Demiris & A. Birk (Eds.), Interdisciplinary approaches to robot learning (pp. 136–161). Singapore: World Scientific Press.Google Scholar