Frederick L. Crabbe IV

Click here for a pdf version of my CV.

Projects

Education

University of California, Los Angeles		Ph.D.		6/00
University of California, Los Angeles		MS		6/96
Dartmouth College		AB		6/92
University of Edinburgh		Philosophy Exchange Program		12/90

Publications

Journal

• Crabbe, F.L. Compromise Strategies for Action Selection plus Appendix, The Philosophical Transactions of the Royal Society, Part B, vol 362, September 2007. (links go to penultimate version, before proofs)
• McMath, S., Crabbe F., Joyner D. Continued fractions and Parallel SQUFOF. International Journal of Pure and Applied Mathematics, 34(1), pp. 19-38, 2007.
• Crabbe, F., Unifying Undergraduate Artificial Intelligence Robotics: Layers Of Abstraction Over Two Channels AI Magazine, 27(1) pp. 23-38, 2006 (the link goes to the penultimate version, before final proofs).
• Bishop, B., Crabbe, F. and Hudock, B., Design of a Low-Cost, Highly Mobile Urban Search and Rescue Robot. Advanced Robotics, 19(8) pp. 797--928, 2005.
• Crabbe, F. L. and Dyer, M. G., Goal Directed Adaptive Behavior in Second-Order Neural Networks: The MAXSON family of architectures. Adaptive Behavior, 8(2), 2001.
• Martin, P., Crabbe, F., et. al., SpeechActs: A Spoken Language Framework.IEEE Computer, 29(7), 1996. (selected in 2001 as a representative "best-of" paper for the first 10 years of Sun Microsystems Laboratories).

Book Chapters

• Crabbe, F.L. Compromise Strategies for Action Selection in Modelling Natural Action Selection, Cambridge University Press, Seth, Bryson and Prescott, Eds. Cambridge University Press, 2011. (This is an extended version of the Royal Society paper above).
• Martin, P., Crabbe, F., et. al., SpeechActs: A Spoken Language Framework. in Sun Microsystems Laboratories: The First Ten Years 1991-2001, Treichel and Holzer, eds. Sun Labs, 2001. (This is a reprint of the IEEE Computer paper above).
• Crabbe, F.L., and Dyer M.G., Goal Directed Adaptive Behavior in Second-Order Neural Networks: Leaning and Evolving in the MAXSON architecture. in Advances in the Evolutionary Synthesis of Intelligent Agents, Honavar and Patel eds. MIT Press, 2001.

Book Reviews

• Crabbe, F.L., Unifying Artificial Intelligence Robotics: An Undergraduate Textbook (in pdf) Adaptive Behavior, 9(2), 2001.
  This is a review of Robin Murphy's Introduction to AI Robotics, published by MIT Press.

Refereed Conference Papers

• Crabbe, F.L,Efficiently finding (nearly) minimal FST of repetitive unsegmented demonstration data to appear in the proceedings of the International Conference on Agents and Artificial Intelligence (ICAART), 2012.
• Lee, M.K., Forlizzi, J., Rybski, P.E., Crabbe, F., Chung, W., Finkle, J., Glaser, E., and Kiesler, S. The Snackbot: Documenting the design of a robot for long-term Human-Robot Interaction. in Proceedings of the 4th International Conference on Human-Robot Interaction (HRI), 2009.
• Crabbe, F.L., On Compromise Strategies for Action Selection with Proscriptive goals in the proceedings of Modeling Natural Action Selection, 2005.
• Crabbe, F.L., Optimal and Non-Optimal Compromise Strategies in Action Selection in the proceedings of the Eighth International Conference on Simulation of Adaptive Behavior (SAB), 2004.
• Hudock, B.M., Bishop, B.E. and Crabbe, F.L., On the Development of a Novel Urban Search and Rescue Robot, in Proceedings of the Thirty-Sixth Southeastern Symposium on System Theory, March 2004, pp. 451 - 455
• Fong, E., Adams, W., Crabbe, F.L., Schultz, A. C., Representing a 3-D Environment with a 2½-D Map Structure, In the proceedings of the International Conference on Intelligent Robotics and Systems (IROS), 2003.
• Crabbe, F.L., On Learning to Select Actions in Multiple Goal Scenariosin the proceedings of the International Conference on Computational Intelligence for Modelling Control and Automation (CIMCA), 2003.
• Crabbe, F.L., Compromise Candidates in Positive Goal Scenariosin the proceedings of the Seventh International Conference on Simulation of Adaptive Behavior (SAB), 2002. A longer version is here.
• Crabbe, F.L., Multiple Goal Q-Learning: Issues and Functions in the proceedings of the International Conference on Computational Intelligence for Modelling Control and Automation (CIMCA), 2001.
• Crabbe, F.L., and Dyer M.G., Observation and Imitation: Goal Sequence Learning in Neurally Controlled Construction Animats: VI-MAXSONin the proceedings of the Sixth International Conference on Simulation of Adaptive Behavior (SAB), 2000.
• Crabbe, F.L., and Dyer M.G., Second-order networks for wall-building agents In the proceedings of the International Joint Conference on Neural Networks (IJCNN), 1999. (won a best of session award)
• Crabbe, F.L., and Dyer, M.G., Vicarious learning in mobile neurally controlled agents: The V-MAXSON architecture. In the proceedings of the International Conference on Artificial Neural Networks (ICANN), 1999.

Education Journals

• C. Brown, F. Crabbe, R. Doerr, R. Greenlaw, C. Hoffmeister, J. Monroe, D. Needham, A. Phillips, S. Schall, J. Schultz, S. Simon, D. Stahl, S. Standard, Anatomy, Dissection, and Mechanics of an Introductory Cyber-Security Class's Curriculum at the United States Naval Academy. To appear in ASEE Computers in Education Journal.

Education Conferences

• Christopher Brown, Frederick Crabbe, Rita Doerr, Raymond Greenlaw, Chris Hoffmeister, Justin Monroe, Donald Needham, Andrew Phillips, Anthony Pollman, Stephen Schall, John Schultz, Steven Simon, David Stahl, Sarah Standard. Anatomy, Dissection, and Mechanics of an Introductory Cyber-Security Class's Curriculum at the United States Naval Academy. 17th Annual Conference on Innovation and Technology in Computer Science Education, pages 303-308, Haifa, Israel, July 2012.
• C. Brown, F. Crabbe, R. Doerr, R. Greenlaw, C. Hoffmeister, J. Monroe, D. Needham, A. Phillips, S. Schall, J. Schultz, S. Simon, D. Stahl, S. Standard, Developing and Implementing an Institution-Wide Introductory Cyber-Security Course in Record Time. In the proceedings of the 50th ACM Southeast Conference, 2012, pp 95-100.
• Crabbe, F.L. Unifying Undergraduate Artificial Intelligence Robotics: Layers Of Abstraction Over Two Channels. In the proceedings of the AAAI Spring Symposium on Hands on Robotics Education, 2004.

Non-peer-reviewed

• Crabbe, R and Dubey, A. eds, Articial Intelligence FAQ: General Questions and Answers. Posted monthly to the moderated newsgroup comp.ai. (now retired).

Invited Talks

• Compromise Strategies for Action Selection. March 3, 2006, Intelligent Systems Program, University of Pittsburgh.
• Unifying Undergraduate Artificial Intelligence Robotics March 22, 2004. AAAI Spring Symposium on Hands on Robotics Education, Stanford University.
• Artificial Intelligence: Where It's Come From, Where It's Going, and Why It's Hard. February 19, 2004, Society of American Military Engineers, Annapolis, MD.
• Undergraduate Robotics: A New Systhesis.April 10, 2003. Olin College of Engineering
• Construction and Learning Among Neurally Controlled Animats. March 29, 2000.  Emory University.
• Learning and Cooperation in Neurally Controlled Agents. March 23, 1999. Intel Reasearch Laboratories.

Other Research Experience