Mixed-Initiative Computing


Dr. Michael T. Cox

Department of Computer Science and Engineering

Wright State University, Ohio





A growing new area of computer science research examines mixed-initiative computation (MIC) between humans and machines.  The research is not simply a subfield of either HCI or human factors engineering/psychology (although many ideas and techniques are borrowed from them); rather the problems and issues of mixed-initiative computation arose principally from the field of artificial intelligence.  Under the MIC umbrella falls three computational areas under the names (1) mixed-initiative planning, (2) mixed-initiative case-based reasoning, and (3) mixed-initiative dialogue.  The first area studies planning techniques that attempt to overcome the computational complexity of fully automated planning by incorporating an active in-the-loop human; the second and third areas emphasize the dynamic shift of control (initiative) between a human and a machine given a problem-solving task.  All three have the main goal of producing better results than either the human or the computer could alone.  This talk will discuss general issues surrounding MIC and current research involved with it in the wider academic community and will provide specific examples from research performed at the Collaboration and Cognition Laboratory in the Department of Computer Science and Engineering at Wright State University. 


Instructor's Biography:

Michael T. Cox is an assistant professor in the Department of Computer Science & Engineering at Wright State University, Dayton, Ohio and is the director of Wright States Collaboration and Cognition Laboratory.  He received his Ph.D. in Computer Science from the Georgia Institute of Technology, Atlanta, in 1996 and his undergraduate degree from the same in 1986.  From 1996 to 1998, he was a postdoctoral fellow in the Computer Science Department at Carnegie Mellon University in Pittsburgh working on mixed-initiative planning.  His research interests include case-based reasoning, collaborative mixed-initiative planning, intelligent agents, understanding (situation assessment), introspection, and learning.  More specifically, he is interested in how goals interact with and influence these broader cognitive processes.  His approach to research follows both artificial intelligence and cognitive science directions.  For more information, see URL: www.cs.wright.edu/~mcox.