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Transfer of Learning for Complex Task Domains: A Demonstration Using Multiple Robots
 

Summary: Transfer of Learning for Complex Task Domains:
A Demonstration Using Multiple Robots
Sameer Singh and Julie A. Adams
Department of Electrical Engineering and Computer Science
Vanderbilt University, Nashville, Tennessee 37235
{sameer.singh, julie.a.adams}@vanderbilt.edu
Abstract-- This paper demonstrates a learning mechanism for
complex tasks. Such tasks may be inherently expensive to learn
in terms of training time and/or cost of obtaining each training
pattern. Learning simple, safe tasks and extending them to more
complex tasks can cause faster convergence to the solution. This
method has been formalized and demonstrated on a simulated
multiple robot (multi-robot) scenario. The objective is to effec-
tively search out and destroy stationary hostile agents present in
an unknown urban terrain map. Using the presented method, the
robots learn how to effectively map the area, and then improve
their learning modules for the complex task. The robots are
simple behavioral agents with minimal communication.
I. INTRODUCTION
This paper aims to improve learning for robots faced with

  

Source: Adams, Julie A. - Department of Electrical Engineering and Computer Science, Vanderbilt University

 

Collections: Engineering; Computer Technologies and Information Sciences