Prasad Tadepalli

Professor
Computer Science
Education: 
  • PhD, Computer Science, Rutgers University, U.S., 1990
  • MTech, Computer Science, Indian Institute of Technology, Madras, India, 1981
  • BTech, Electrical Engineering, Regional Engineering College, Warangal, India, 1979
Biography: 

Prasad Tadepalli has an M. Tech in Computer Science from Indian Institute of Technology, Madras, India and a Ph.D. from Rutgers University, New Brunswick. He joined Oregon State University, Corvallis, as an assistant professor in 1989. He is now a professor in the School of Electrical Engineering and Computer Science of Oregon State University.

He co-authored over a hundred papers in Artificial Intelligence and Machine Learning in various journals, conferences, and workshops. He organized many workshops and tutorials and co-chaired the international conference on inductive logic programming in 2007. He was a member of many conference program committees and is currently an action editor for the Journal of Artificial Intelligence Research, and the Machine Learning journal.

Research Interests: 

Research Areas
Artificial Intelligence, Machine Learning, Automated Planning and Reasoning, Natural Language Processing.

Research Description
My main research interest is to understand learning and thinking by simulating them in computers. My work ranges from theoretical analyses of learning problems and algorithms to their implementation, evaluation, and application to real-world problems.

One of my research thrusts is to learn to act intelligently by building models of actions, planning or reasoning with them, executing the plans, and learning better models and ways to plan with them. There are several interesting questions here such as how to model only what is needed, how to account for errors in the models, how best to combine knowledge and search in planning, how to learn from observation as well as practice, how to exploit hierarchies in planning and learning, and how to transfer knowledge from one domain to a related domain.

Another research thrust is to learn in structured contexts such as natural language processing where the examples have rich internal structure, and are noisy, incomplete, biased, and highly interconnected.

The interesting issues here include learning in expressive representations, learning multiple related concepts simultaneously, constraining learning by explicit prior knowledge, accounting for bias and incompleteness in the data, and integrated learning and reasoning.

Applications of Research
The applications of research include fire and medical emergency response, learning and training systems for expert tasks, intelligent assistants for disabled and elderly, and personalized medicine.

2013
Joshi, S., R. Khardon, P. Tadepalli, A. Raghavan, and A. Fern, "Solving Relational MDPs with Exogenous Events and Additive Rewards", European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD-2013), vol. 8188, Prague, Czech Republic, Springer Berlin Heidelberg, pp. 178 - 193, 09/2013. Abstract
2012
Wilson, A., A. Fern, and P. Tadepalli, "Transfer Learning in Sequential Decision Problems: A Hierarchical Bayesian Approach", Journal of Machine Learning Research - Proceedings Track, vol. 27, pp. 217-227, 2012.
Wilson, A., A. Fern, and P. Tadepalli, "A Bayesian Approach for Policy Learning from Trajectory Preference Queries", Advances in Neural Information Processing Systems (NIPS-2011) , Lake Tahoe, Nevada, pp. 1142–1150, 12/2012. Abstract
Natarajan, S., P. Tadepalli, and A. Fern, "A relational hierarchical model for decision-theoretic assistance", Knowledge and Information Systems, vol. 32, no. 2: Springer-Verlag, pp. 329-349, 08/2012. Abstract
Raghavan, A., S. Joshi, A. Fern, P. Tadepalli, and R. Khardon, "Planning in Factored Action Spaces with Symbolic Dynamic Programming", Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-2012), Toronto, Ontario, Canada, 07/2012. Abstract
Doppa, J. R., A. Fern, and P. Tadepalli, "Output Space Search for Structured Prediction", 29th International Conference on Machine Learning (ICML 2012), Edinburgh, Scotland, 06/2012. Abstract
2011
Mehta, N., P. Tadepalli, and A. Fern, "Autonomous Learning of Action Models for Planning", Advances in Neural Information Processing Systems (NIPS-2011), Granada, Spain, pp. 2465-2473, 12/2011. Abstract
Sorower, S., T. G. Dietterich, J. R. Doppa, W. Orr, P. Tadepalli, and X. Z. Fern, "Inverting Grice's Maxims to Learn Rules from Natural Language Extractions", 2011 Conference on Neural Information Processing Systems (NIPS-2011), Granada, Spain, pp. 1053-1061, 12/2011. Abstract
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Fern, A., R. Khardon, and P. Tadepalli, "The first learning track of the international planning competition", Machine Learning, vol. 84, issue 1-2, pp. 81 - 107, 07/2011. Abstract
Sorower, M. S., T. G. Dietterich, J. R. Doppa, P. Tadepalli, and X. Z. Fern, "Learning Rules from Incomplete Examples via a Probabilistic Mention Model", IJCAI 2011 Workshop on Learning by Reading and its Applications in Intelligent Question-Answering, Barcelona, Catalonia, Spain, 07/2011. Abstract
Doppa, J. R., M. NasrEsfahani, M. S. Sorower, J. Irvine, T. G. Dietterich, X. Z. Fern, and P. Tadepalli, "Learning Rules from Incomplete Examples via Observation Models", IJCAI 2011 Workshop on Learning by Reading and its Applications in Intelligent Question-Answering, Barcelona, Catalonia, Spain, 07/2011. Abstract
2010
Fern, A., and P. Tadepalli, "A Computational Decision Theory for Interactive Assistants", Advances in Neural Information Processing Systems (NIPS-2010), Vancouver, B.C., Canada, pp. 577–585, 12/2010. Abstract
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Wilson, A., A. Fern, and P. Tadepalli, "Incorporating Domain Models into Bayesian Optimization for RL", European Conference on Machine Learning (ECML-10), Barcelona, Spain, pp. 467-482, 09/2010. Abstract
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Wilson, A., A. Fern, and P. Tadepalli, "Bayesian role discovery for multi-agent reinforcement learning", International Conference on Autonomous Agents and Multiagent Systems (AAMAS-10), Toronto, Canada, pp. 1587-1588, 05/2010. Abstract
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2009
Bjarnason, R., A. Fern, and P. Tadepalli, "Lower Bounding Klondike Solitaire with Monte-Carlo Planning", International Conference on Automated Planning and Scheduling (ICAPS-2009), Thessaloniki, Greece, 09/2009. Abstract

Best Student Paper of ICAPS (International Conference on Automated Planning and Scheduling)

Zhang, X., S. Yoon, P. DiBona, D. S. Appling, L. Ding, J. R. Doppa, D. Green, J. K. Guo, U. Kuter, G. Levine, et al., "An Ensemble Learning and Problem-Solving Architecture for Airspace Management", Proceedings of Twenty-First Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-09), Pasadena, CA, pp. 203-210, 07/2009. Abstract
Bjarnason, R., P. Tadepalli, A. Fern, and C. Niedner, "Simulation-based Optimization of Resource Placement and Emergency Response", Conference on Innovative Applications of Artificial Intelligence (IAAI-2009), Pasadena, California, pp. 47-53, 07/2009. Abstract