Transfer of Learned Knowledge in
Life-Long Learning Agents

Joseph O'Sullivan, Carnegie Mellon University

Previous work has demonstrated that the performance of machine learning algorithms can be improved by exploiting various forms of knowledge, such as domain theories. More recently, it has been recognized that some forms of knowledge can in turn be learned -- in particular, action models and task-specific internal representations. Using learned knowledge as a source of learning improvement can be particularly appropriate for agents that face many tasks. Over a long lifetime, an agent can amortize effort expended in learning knowledge by reducing the number of examples required to learn further tasks. In developing such a ``life-long learning'' agent, a number of research issues arise, including: will an agent benefit from learned knowledge, can an agent exploit multiple sources of learned knowledge, how should the agent adapt as a new task arrives, how might the order of task arrival impact learning, and how can such an agent be built?

I propose that an agent can be constructed which learns knowledge and exploits that knowledge to effectively improve further learning by reducing the number of examples required to learn. I intend to study the transfer of learned knowledge by life-long learning agents within a neural network based architecture capable of increasing capacity with the number of tasks faced. This proposal describes an appropriate architecture, based on preliminary work in controlled settings. This work has shown that learned knowledge can reduce the number of examples required to learn novel tasks and that combining previously separate mechanisms can yield a synergistic improvement on learning ability. It has also explored how capacity can be expanded as new tasks arise over time and how the order in which tasks arise can be exploited with a graded curriculum. This preliminary work will be applied to a life-long learning agent and extended by carrying out experimental studies of a simulated robot agent in a controlled environment and of a real-world mobile robot agent in Wean Hall.

Joseph Kieran O'Sullivan
Last modified: Mon Aug 25 20:54:59 EDT 1997