Goal-Driven Learning (GDL) views learning as a strategic process in which the learner attempts to identify
and satisfy its learning needs in the context of its tasks and goals. This is modeled as a planful process
where the learner analyzes its reasoning traces to identify learning goals, and composes a set of learning
strategies (modeled as planning operators) into a plan to learn by satisfying those learning goals.
Traditional GDL frameworks were based on traditional planners. However, modern AI systems often deal
with real-time scenarios where learning and performance happen in a reactive real-time fashion, or are
composed of multiple agents that use different learning and reasoning paradigms. In this talk, I will
discuss new GDL frameworks that handle such problems, incorporating reactive and multi-agent planning
 techniques in order to manage learning in these kinds of AI systems.
 
BIO
Dr. Ashwin Ram is an Associate Professor and Director of the Cognitive Computing Lab in the College

of Computing at Georgia Tech, an Associate Professor of Cognitive Science, and an Adjunct Professor

in Psychology at Georgia Tech and in MathCS at Emory University. He received his PhD from Yale

University in 1989, his MS from University of Illinois in 1984, and his BTech from IIT Delhi in 1982.

He has published 2 books and over 100 scientific articles in international forums. He is a founder

of Enkia Corporation which provides AI software for information assurance and decision support.

 (www.cc.gatech.edu/faculty/ashwin)