I do research on artificial intelligence, in particular on planning and machine
learning, and their combination. Research on AI planning designs, develops, and
analyzes computer programs that generate sequence of actions that an agent (for
example a robot or the machines in a machine shop) must follow in order to
achieve a goal. Machine Learning for planning systems builds programs that
improve the performance of planners, by increasing their efficiency (building
plans faster), by increasing the quality of the plans (according to some
problem-dependent quality metric), or by developing and refining the planner's
model of the actions available in the world. In particular I use
an AI planning and learning system developed at Carnegie Mellon as a research
I finished my PhD from Carnegie Mellon
University, School of
Computer Science in July 1996.
Here you can find an abstract of my PhD thesis on
Learning search control knowledge to improve plan quality.
Extended list of publications