Autonomic Computing
Autonomic Computing studies techniques for making computing systems self-configuring, self-tuning, self-diagnosing, self-repairing, and self-protecting. Our current work in the area focuses on using machine learning techniques to allow computing systems to configure and tune themselves to adapt to changing workloads and to automatically acquire patterns for detecting and blocking Internet worms.
People
Peter Stone Faculty pstone [at] cs utexas edu
Publications
Diagnosis and Reconfiguration using Bayesian Networks: An Electrical Power System Case Study 2009
W. Bradley Knox and Ole Mengshoel, In IJCAI 2009 Workshop on Self-* and Autonomous Systems 2009.
Autonomous Return on Investment Analysis of Additional Processing Resources 2007
Jonathan Wildstrom, Peter Stone, and Emmett Witchel, In 2007 Workshop on Adaptive Methods in Autonomic Computing Systems, June 2007.
Machine Learning for On-Line Hardware Reconfiguration 2007
Jonathan Wildstrom, Peter Stone, Emmett Witchel, and Mike Dahlin, In The 20th International Joint Conference on Artificial Intelligence, pp. 1113-1118, January 2007.
Adapting to Workload Changes Through On-The-Fly Reconfiguration 2006
Jonathan Wildstrom, Peter Stone, Emmett Witchel, and Mike Dahlin, Technical Report UT-AI-TR-06-330, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory.
Fast and Effective Worm Fingerprinting via Machine Learning 2006
Stewart Yang, Jianping Song, Harish Rajamani, Taewon Cho, Yin Zhang and Raymond Mooney, Technical Report AI-06-335, Artificial Intelligence Lab, The University of Texas at Austin. This is a longer version of our ICAC-2006 paper.
Fast and Effective Worm Fingerprinting via Machine Learning 2006
Stewart Yang, Jianping Song, Harish Rajamani, Taewon Cho, Yin Zhang and Raymond Mooney, In Proceedings of the 3rd IEEE International Conference on Autonomic Computing (ICAC-2006), Dublin, Ireland, June 2006. Poster Session.
Towards Self-Configuring Hardware for Distributed Computer Systems 2005
Jonathan Wildstrom, Peter Stone, E. Witchel, Raymond Mooney and M. Dahlin, In The Second International Conference on Autonomic Computing, pp. 241-249, June 2005.
Adaptive Job Routing and Scheduling 2004
Shimon Whiteson and Peter Stone, Engineering Applications of Artificial Intelligence, Vol. 17(7), 7 (2004), pp. 855-869. Corrected version.
Labs
Machine Learning Learning Agents