סמינר מחלקתי

School of Mechanical Engineering Seminar
Monday, December 29, 2014 at 15:00
Wolfson Building of Mechanical Engineering, Room 206

Family Bootstrapping: a Genetic Transfer Learning Approach for Onsetting the Evolution for a Set of Related Robotic Tasks

Amiram Moshaiov

School of Mechanical Engineering, Faculty of Engineering

Tel Aviv University, Israel

Studies on the bootstrap problem in evolutionary robotics help lifting the barrier from the way to evolve robots for complex tasks. It remains an open question, though, how to reduce the need for designer knowledge when devising a bootstrapping approach for any particular complex task. Recent developments in the field of transfer learning may help reducing this need and support the evolution of solutions to complex tasks, through task relatedness. Relying on the commonalities of similar tasks, we introduce a new concept of Family Bootstrapping (FB). FB refers to the creation of biased ancestors that are expected to onset the evolution of "a family" of solutions not just for one task, but for a set of related robot tasks. A general FB paradigm is outlined and the unique potential of the proposed concept is discussed. To highlight the validity of the FB concept, a simple demonstration case, concerning the evolution of neuro-controllers for a set of robot navigation tasks, is provided. The FB concept resulted from an earlier work on bootstrapping the co-evolution of soccer-like players, which is also briefly reported.  The presentation is concluded with some suggestions for future research.