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Two Approaches to Implementing Metacognition

Authors:
Emily Hand
Darsana Josyula
Matthew Paisner
Elizabeth McNany
Donald Perlis
Michael Cox

Keywords: Metacognition; Dialog Management

Abstract:
Abstract—Metacognition, the ability to monitor and regulate cognition, is important for an agent to adapt to novel situations and fix discrepancies in its knowledge base. In this paper, we discuss two different approaches to implementing metacognition in artificial systems: internally and externally. In the internal approach, metacognition is built into the agent, and thus, is combined with its cognitive reasoning abilities. The same Knowledge Base (KB) is fully shared between the metacognitive and cognitive processes of the artificial system. In the external metacognition approach, only portions of the agent’s KB are shared between the agent and the external metacognition. We describe the implementation of external metacognition using our own Metacognitive Loop (MCL2) and internal metacognition using active logic in the context of a dialog agent called Alfred. We discuss how the two systems handle long pauses in dialog and compare the pros and cons of each. Our experiments show that for a system with time-related expectations, it is more efficient to use interleaved metacognition rather than an external metacognition module as the internal metacognition has access to the entire KB of the agent.

Pages: 45 to 50

Copyright: Copyright (c) IARIA, 2014

Publication date: May 25, 2014

Published in: conference

ISSN: 2308-4197

ISBN: 978-1-61208-340-7

Location: Venice, Italy

Dates: from May 25, 2014 to May 29, 2014