Erik Mueller

Erik Mueller

     Research Staff Member, IBM Watson Group and IBM Research

Erik Mueller (LinkedIn)


I am a member of the IBM team that developed Watson, a natural language question answering system that won a two-game Jeopardy! match against two Jeopardy! grand champions. With the team I am currently developing Watson for Healthcare, which will help healthcare professionals diagnose, treat, and manage patients.

The overall goal of my research in artificial intelligence is to automate commonsense reasoning to make computers more helpful to people. Commonsense reasoning is important because it allows computer systems to be more aware of the human world, more flexible in the face of surprises, and more responsive to user needs.

I developed the discrete event calculus to improve the efficiency of automated commonsense reasoning using the event calculus, a logical formalism for reasoning about action and change. I developed the open source Discrete Event Calculus Reasoner and wrote the book Commonsense Reasoning, a comprehensive guide to the field for researchers and students.

I also developed DAYDREAMER, a cognitive architecture that models human daydreaming, and ThoughtTreasure, a commonsense knowledge base and architecture for natural language processing.

I received my S.B. in Computer Science and Engineering from the Massachusetts Institute of Technology and my M.S. and Ph.D. in Computer Science from the University of California, Los Angeles.


News


Books

How can computers reason about everyday events and situations? Commonsense Reasoning How can computers understand language? Natural Language Processing with ThoughtTreasure
What would it be like to speak fluent French? Fluent French How can computers daydream? Daydreaming in Humans and Machines


Publications

  1. Ferrucci, David,  Levas, Anthony,  Bagchi, Sugato,  Gondek, David,  & Mueller, Erik T. (2013). Watson: Beyond Jeopardy! Artificial Intelligence, 199-200, 93-105.
  2. Hajishirzi, Hannaneh, & Mueller, Erik T. (2012). Question answering in natural language narratives using symbolic probabilistic reasoning. In H. Chad Lane, G. Michael Youngblood, & Philip McCarthy (Eds.), Proceedings of the Twenty-Fifth International Florida Artificial Intelligence Research Society Conference. Menlo Park, CA: AAAI Press.
  3. Hajishirzi, Hannaneh,  Amir, Eyal,  Mueller, Erik T.,  & Hockenmaier, Julia (2011). Reasoning about RoboCup soccer narratives. Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial Intelligence. Corvallis, Oregon: AUAI Press.
  4. Hajishirzi, Hannaneh, & Mueller, Erik T. (2011). Symbolic probabilistic reasoning for narratives. In Ernest Davis, Patrick Doherty, & Esra Erdem (Eds.), Logical Formalizations of Commonsense Reasoning: Papers from the 2011 AAAI Spring Symposium. Technical Report SS-11-06. Menlo Park, CA: AAAI Press.
  5. Finlayson, Mark,  Gervás, Pablo,  Mueller, Erik T.,  Narayanan, Srini,  & Winston, Patrick (Eds.). (2010). Computational Models of Narrative: Papers from the 2010 AAAI Fall Symposium. Technical Report FS-10-04. Menlo Park, CA: AAAI Press.
  6. Mueller, Erik T. (2009). Automating commonsense reasoning using the event calculus. Communications of the ACM, 52(1), 113-117.
  7. Havasi, Catherine,  Lieberman, Henry,  & Mueller, Erik T. (2009). CSIUI 2009: Story understanding and generation for aware and interactive interface design. Proceedings of the 2009 International Conference on Intelligent User Interfaces (p. 491). New York: Association for Computing Machinery.
  8. Mueller, Erik T. (2008). Event calculus. In Frank van Harmelen, Vladimir Lifschitz, & Bruce Porter (Eds.), Handbook of Knowledge Representation (pp. 671-708). Amsterdam: Elsevier.
  9. Mueller, Erik T. (2007). Modelling space and time in narratives about restaurants. Literary and Linguistic Computing, 22(1), 67-84.
  10. Hillis, Danny,  McCarthy, John,  Mitchell, Tom M.,  Mueller, Erik T.,  Riecken, Doug,  Sloman, Aaron,  & Winston, Patrick Henry (2007). In honor of Marvin Minsky's contributions on his 80th birthday. AI Magazine, 28(4), 103-110.
  11. Mueller, Erik T. (2007). Understanding goal-based stories through model finding and planning. In Brian S. Magerko & Mark O. Riedl (Eds.), Intelligent Narrative Technologies: Papers from the AAAI Fall Symposium (pp. 95-101). Technical Report FS-07-05. Menlo Park, CA: AAAI Press.
  12. Mueller, Erik T. (2007). Discrete event calculus with branching time. In Eyal Amir, Vladimir Lifschitz, & Rob Miller (Eds.), Logical Formalizations of Commonsense Reasoning: Papers from the 2007 AAAI Spring Symposium (pp. 126-131). Technical Report SS-07-05. Menlo Park, CA: AAAI Press.
  13. Mueller, Erik T. (2006). Commonsense Reasoning. San Francisco: Morgan Kaufmann/Elsevier.
  14. Mueller, Erik T. (2006). Event calculus and temporal action logics compared. Artificial Intelligence, 170(11), 1017-1029.
  15. Mueller, Erik T., & Sutcliffe, Geoff (2005). Reasoning in the event calculus using first-order automated theorem proving. In Ingrid Russell & Zdravko Markov (Eds.), Proceedings of the Eighteenth International Florida Artificial Intelligence Research Society Conference (pp. 840-841). Menlo Park, CA: AAAI Press.
  16. Mueller, Erik T., & Sutcliffe, Geoff (2005). Discrete event calculus deduction using first-order automated theorem proving. In Boris Konev & Stephan Schulz (Eds.), Proceedings of the Fifth International Workshop on the Implementation of Logics (pp. 43-56). Montevideo, Uruguay. Technical Report ULCS-05-003, Department of Computer Science, University of Liverpool.
  17. Mueller, Erik T. (2004). Event calculus reasoning through satisfiability. Journal of Logic and Computation, 14(5), 703-730.
  18. Mueller, Erik T. (2004). Understanding script-based stories using commonsense reasoning. Cognitive Systems Research, 5(4), 307-340.
  19. Mueller, Erik T. (2004). A tool for satisfiability-based commonsense reasoning in the event calculus. In Valerie Barr & Zdravko Markov (Eds.), Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference (pp. 147-152). Menlo Park, CA: AAAI Press.
  20. Mueller, Erik T. (2003). Story understanding through multi-representation model construction. In Graeme Hirst & Sergei Nirenburg (Eds.), Text Meaning: Proceedings of the HLT-NAACL 2003 Workshop (pp. 46-53). East Stroudsburg, PA: Association for Computational Linguistics.
  21. McCarthy, John,  Minsky, Marvin,  Sloman, Aaron,  Gong, Leiguang,  Lau, Tessa,  Morgenstern, Leora,  Mueller, Erik T.,  Riecken, Doug,  Singh, Moninder,  & Singh, Push (2002). An architecture of diversity for commonsense reasoning. IBM Systems Journal, 41(3), 530-539.
  22. Mueller, Erik T. (2002). Story understanding. In Lynn Nadel (Ed.), Encyclopedia of Cognitive Science (Vol. 4, pp. 238-246). London: Nature Publishing Group.
  23. Singh, Push,  Lin, Thomas,  Mueller, Erik T.,  Lim, Grace,  Perkins, Travell,  & Zhu, Wan Li (2002). Open Mind Common Sense: Knowledge acquisition from the general public. In Robert Meersman & Zahir Tari (Eds.), Lecture Notes in Computer Science: Vol. 2519. On the Move to Meaningful Internet Systems 2002: DOA/CoopIS/ODBASE 2002 (pp. 1223-1237). Berlin: Springer.
  24. Mueller, Erik T. (2001). Machine-understandable news for e-commerce and web applications. Proceedings of the 2001 International Conference on Artificial Intelligence (pp. 1113-1119). CSREA Press.
  25. Mueller, Erik T. (2000). A calendar with common sense. Proceedings of the 2000 International Conference on Intelligent User Interfaces (pp. 198-201). New York: Association for Computing Machinery.