Goal-directed Metacontrol for Integrated Procedure Learning

SRI authors: ,


Kim, J. and Myers, K. and Gervasio, M. and Gil, Y. . Goal-directed Metacontrol for Integrated Procedure Learning in Metareasoning: Thinking about thinking, MIT Press, 2010.


Developing systems that learn how to perform complex tasks presents a significant challenge to the artificial intelligence community. As the knowledge to be learned becomes complex, with diverse procedural constructs and uncertainties to be validated, the system needs to integrate a wide range of learning and reasoning methods with different focuses and strengths. For example, one learning method may be used to generalize from user demonstrations, another to learn by practice and exploration, and another to test hypotheses with experiments. The POIROT system pursues such a multistrategy learning methodology that employs multiple integrated learners and knowledge validation modules to acquire complex process knowledge for a medical logistics domain
(Burstein et al., 2008).

We describe a metalevel framework for coordinating the activities of a community of learners to create an integrated learning system. The metalevel framework is organized around learning goals, which are formulated through introspective reasoning to identify problems and requirements for the ongoing learning process. These learning goals are posted to a shared blackboard to direct the other components in the system. Goals can be either process or knowledge oriented.

Keywords: Artificial Intelligence, Artificial Intelligence Center, AIC, learning by demonstration, learning ensembles, question asking, workflow

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