I am the John L. Tishman Professor of Engineering in the Computer Science and Engineering Division of the Electrical Engineering and Computer Science Department of the College of Engineering at the University of Michigan.
I received my B.S. from the University of Michigan in 1975 and my Ph.D. in Computer Science from Carnegie Mellon University in 1983. My thesis advisor was Allen Newell. I was a member of research staff at Xerox Palo Alto Research Center from 1984 to 1986.
Since 1986, I have been on the faculty of the Computer Science and Engineering Division of the Electrical Engineering and Computer Science Department of the University of Michigan where I am a Professor. I am a founder of Soar Technology, an Ann Arbor company specializing in creating autonomous AI entities. I am a fellow of the Association for the Advancement of Artificial Intelligence (AAAI), ACM, the Cognitive Science Society, and the American Association for the Advancement of Science (AAAS).
I have been awarded the 2018 Herbert A. Simon Prize for Advances in Cognitive Systems along with my long-time collaborator Prof. Paul Rosenbloom of the University of Southern California. This award recognizes our research on cognitive architectures, especially the Soar project, and their applications to knowledge-based systems and models of human cognition, and our contributions to theories of representation, reasoning, problem solving, and learning.
My major research interest is in creating human-level artificial intelligent entities, with an emphasis on the underlying cognitive architecture. A major challenge is to create systems that can work on a broad range of problems, using a wide variety of methods, knowledge, and learning techniques. As part of my research, I study both artificial and natural intelligence. Since 1981, my work has centered on the development and use of Soar, a general cognitive architecture. Over the years, this has led to research in both AI and cognitive science. Within AI my work has included research in general problem solving, the genesis of the weak methods, the origins of subgoals, general learning mechanisms, interacting with external environments, learning by experience and by instruction, and integrating reactivity, planning, and learning, all in the service of constructing complete autonomous intelligent agents. In the past, I’ve done some work on developing human-level AI agents for military simulations, interactive computer games, and most recently autonomous robotics. Within cognitive science, my early research has concentrated on detailed modeling of human behavior (reaction times and error rates) in visual attention, concept acquisition, and dual tasks. Currently I’m concentrating on high-level cognition. Most recently, my students and I have extended Soar to include reinforcement learning, episodic memory, semantic memory, mental imagery, and emotion-inspired processing. We are exploring interactive task learning by developing agents in Soar that learn new tasks from scratch using natural language. The tasks involve real-world robotic interaction and include hierarchical tasks, as well as many simple puzzles and games.
Recent publications can be found on the Soar website.
Our interactive task learning project, which includes a collection of articles, videos, and other resources: https://soargroup.github.io/rosie/
The best resources for learning about Soar:
- Laird, J. E. 2012. The Soar Cognitive Architecture, MIT Press, Cambridge, MA
- The Soar Tutorial on the Soar website.
My long lost computer game, Haunt, implemented as 1500 rules in OPS4 is back!
“The secret to success is constancy of purpose.”