CALO Explanation Project Page  The CALO Explanation project
provided explanation capabilities for various components in
CALO. Through the Integrated Cognitive Explanation Environment
(ICEE), this project enabled CALO to explain its task processing
and task learning abilities, to aid in building user trust. This
work was mainly conducted at Stanford University, Rensselaer
Polytechnic Institute (RPI), and SRI International, under the
primary guidance of Deborah L. McGuinness.  Research Team
Deborah L. McGuinness, RPI (PI) Alyssa Glass, Stanford Michael
Wolverton, SRI Paulo Pinheiro da Silva, UTEP Cynthia Chang, RPI
Li Ding, RPI  Project Overview  CALO, as an adaptive agent, is
incredibly complex. It includes task processors, hybrid theorem
provers, and probabilistic inference engines; multiple learning
components employing a wide range of logical and statistical
techniques; and multiple heterogeneous, distributed information
sources underlying the processing. Despite the sophistication,
however, individual CAL