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From Brain Science to Intelligent Machines

Experience-based goal generation and motivated reinforcement learning for a mobile robot

Date: Thursday 23/01/2014
Venue: MS020
Time: 1.00 pm
Speaker: Dr Kathryn E. Merrick
Affiliation: University of New South Wales, Australian Defence Force Academy, Canberra, ACT, Australia


Experience-based goal generation and motivated reinforcement learning for a mobile robot


By

Dr Kathryn E. Merrick

Senior Lecturer in Information Systems and Computer Science

University of New South Wales, Australian Defence Force Academy, Canberra, ACT, Australia

Abstract:
Learning skills online from experiences is attractive for robots because it permits a robot to develop its skills autonomously. However, the onus lies with the system designer to specify which skills the robot should learn. Experience-based goal generation algorithms permit a robot to decide autonomously which skills to learn. However, such algorithms have not been widely explored in robotics. This talk presents an approach to experience-based generation of achievement and maintenance goals for a mobile robot and discusses how these goals can be used to motivate learning. The talk will cover the design of an experience-based goal generation algorithm and experimental analysis of the algorithm for generating different types of goals. A selection of reinforcement learning algorithms for learning skills to solve self-motivated goals will also be discussed.

Short biography:
Dr Kathryn E. Merrick, received Bachelor degree in Computer Science and Technology (Advanced, Honours I, University Medal) at University of Sydney, NSW, Australia, 2002; PhD in Computer Science from National ICT Australia and University of Sydney, NSW, Australia, 2007. 
Dr Merrick is a Senior Lecturer in Information Systems and Computer Science at the University of New South Wales, Australian Defence Force Academy, Canberra, ACT, Australia. Her research interests lie in the broad areas of artificial intelligence and machine learning, with applications in virtual characters, developmental robotics and intelligent environments. Her research is principally concerned with the development of algorithms and metrics for self-motivated learning agents. She is co-author of the book Motivated Reinforcement Learning: Curious Characters for Multiuser Games (Berlin: Springer-Verlag, 2009) and over forty refereed conference and journal papers.

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