"It is important to create an environment where students can learn the problem-solving techniques that will help them to go beyond the thoughtful use of established applications into the realm of scientific discovery." Gary Parker

• Artificial intelligence
• Cognitive science
• Autonomous agent learning
• Colony robotics
• Evolutionary robotics
• Genetic algorithms
• Multi-legged robots
• Interactive video games

Professor Parker's research focuses on methodologies for learning in autonomous agents. Currently he is concentrating on evolutionary robotics, where he is applying evolutionary computation to generate control programs for legged robots, and video game agent learning, where he uses Xpilot-AI as a test environment for evolving control programs.

He developed the cyclic genetic algorithm (CGA), which is a variant of the standard GA, to provide a means for learning cycles of behavior. CGAs have been tested on three different levels of control complexity (individual leg cycles, gaits, and search cycles). In addition, he developed punctuated anytime learning (PAL), which he is using to incorporate CGAs into a real-time learning system that uses periodic tests on the robot to continually improve the quality of controller learning. This new way of integrating the actual robot with its simulation during evolutionary computation allows the system to make adjustments to the onboard controller while learning is carried out off line, giving the robot the capability to adapt to changes in real time. Additional research has resulted in a method using PAL and sampling to co-evolve cooperative individuals in a team of robots. He also led the creation of Xpilot-AI, a system based on Xpilot (an open-source 2D multiplayer space combat game, playable over the internet) that was developed as a test-bed for agent control learning methods.

Future research plans include expanded experimentation with colony robotics, Xpilot-AI, genetic algorithms, emergent systems, neural networks, and collaborations with other departments such as Cognitive Science/ Psychology and Biology in the study of locomotion and lower levels of animal cognition.

Professor Parker believes in incorporating research into the classroom and strongly encourages undergraduate research. Since the robots and controllers used are generally inexpensive and of simple construction, students in robotics courses and doing research get hands-on experience in the development of robots and the programming of their controllers. These experiences allow students to observe the results of their labors in real world robotics instead of just in simulation. Students gain valuable problem solving techniques and an appreciation for some of the complexities involved in robotics. Xpilot-AI, which is a free and open source program, is also used in courses and undergraduate research. Read the news story, "Students - and robots - learn in professor's lab."

Professor Parker will teach the Science Leaders First Year Seminar, "Robotics and Problem Solving," in fall 2011.

Professor Parker was presented with the World Automation Congress / AutoSoft Lifetime Achievement Award in October 2008. He has over 70 peer reviewed publications, including conference papers (two of which received best paper awards), journal articles, and book chapters. He was the chair of the 7th and 8th International Symposium on Intelligent Automation and Control (ISIAC2008 and ISIAC2010); has been on the program committee for over 40 conferences; served as a reviewer for 12 journals; is on the board of associate editors for the IEEE Systems Journal and AutoSoft, the International Journal on Intelligent Automation and Soft Computing; and is a member of three IEEE Computational Intelligence Society task forces. His papers and professional activities can be viewed on his personal homepage.