Publications by Leemon Baird

Publications by Leemon Baird

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Most of my publications are available in PDF, Postscript and HTML, each with its source file (either LaTeX or RTF (Microsoft Word)). This bibliography can be listed in several different formats. Please tell me if there are any problems downloading or viewing them.

17 Feb 2005

Baird, L. C., Harmon, M. E., Young, R. R., & Armstrong, J. E. (2004). "US Patent #6,732,278: Apparatus and method for authenticating access to a network resource".
[21 pages: HTML | images]
Moore, A. W., Baird, L. C., & Kaelbling, L. P. (1999). "Multi-Value-Functions: Efficient Automatic Action Hierarchies for Multiple Goal MDPs". Proceedings of the International Joint Conference on Artificial Intelligence.
[6 pages: pdf | ps.gz]
Munos, R. ., Baird, L. C., & Moore, A. W. (1999). "Gradient Descent Approaches to Neural-Net-Based Solutions of the Hamilton-Jacobi-Bellman Equation". Proceedings of the International Joint Conference on Neural Networks.
[6 pages: pdf | ps.gz]
Baird, L. C., & Moore, A. W. (1999). "Gradient descent for general reinforcement learning". Advances in Neural Information Processing Systems 11.
[7 pages: ps.gz | pdf | rtf | HTML]
Baird, L. C. (1999). Reinforcement Learning Through Gradient Descent. (Technical Report CMU-CS-99-132). Computer Science Department, Carnegie Mellon University. (PhD Thesis, Carnegie Mellon University, Pittsburgh, PA).
[78 pages: pdf | ps.gz | rtf]
Weaver, S. E., Baird, L. C., & Polycarpou, M. M. (1998). An Analytical Framework for Local Feedforward Networks. IEEE Transactions on Neural Networks. 9(3).(Also published as Univeristy of Cincinnati Technical Report TR 195/07/96/ECECS).
[23 pages: pdf | ps.gz | tar.gz]
Weaver, S. E., Baird, L. C., & Polycarpou, M. M. (1998). "Preventing unlearning during on-line training of feedforward networks". Proceedings of the International Symposium of Intelligent Control Gaithersburg, MD Sept 14-17.
[6 pages: pdf | ps.gz | tar.gz]
Baird, L. C. (1997). "US Patent #5,608,843: Learning controller with advantage updating algorithm".
[25 pages: HTML | images]
Harmon, M. E., Baird, L. C., & Klopf, A. H. (1996). Reinforcement Learning: An Alternative Approach to Machine Intelligence. CrossTalk, The Journal of Defense Software Engineering. 9(2).
[7 pages: pdf | ps.gz | rtf | HTML]
Bandera, C. ., Vico, F. J., Bravo, J. M., Harmon, M. E., & Baird, L. C. (1996). "Residual Q-learning applied to visual attention". Proceedings of the Thirteenth International Conference on Machine Learning, Bari, Italy, 3-6 July.
[10 pages: pdf | rtf | ps.gz | HTML]
Weaver, S. E., Baird, L. C., & Polycarpou, M. M. (1996). "An analytical framework for local feedforward networks". International Symposium of Intelligent Control, Dearborn, MI, Sept 15-18.
[6 pages: ps.gz | pdf | LaTeX.tar.gz | HTML]
Weaver, S. E., Baird, L. C., & Polycarpou, M. M. (1996). "Local feedforward networks". Adaptive Distributive Parallel Computing, Dayton, OH, Aug 8-9.
[11 pages: ps.gz | pdf | LaTeX.tar.gz | HTML]
Harmon, M. E., & Baird, L. C. (1996). Spurious Solutions to the Bellman Equation. (Technical Report WL-TR-96-'To Be Assigned'). Wright-Patterson Air Force Base Ohio: Wright Laboratory. (Available from the Defense Technical Information Center, Cameron Station, Alexandria, VA 22304-6145).
[8 pages: pdf | ps.gz | rtf | HTML]
Harmon, M. E., & Baird, L. C. (1996). Metrics for Temporal Difference Learning. (Technical Report WL-TR-96-1153). Wright-Patterson Air Force Base Ohio: Wright Laboratory. (Available from the Defense Technical Information Center, Cameron Station, Alexandria, VA 22304-6145).
[7 pages: pdf | ps.gz | rtf | HTML]
Harmon, M. E., & Baird, L. C. (1996). Multi-player residual advantage learning with general function approximation. (Technical Report WL-TR-1065). Wright-Patterson Air Force Base Ohio: Wright Laboratory. (Available from the Defense Technical Information Center, Cameron Station, Alexandria, VA 22304-6145).
[12 pages: pdf | ps.gz | rtf | HTML]
Harmon, M. E., Baird, L. C., & Klopf, A. H. (1995). Reinforcement Learning Applied to a Differential Game. Adaptive Behavior. 4(1).
[28 pages: pdf | ps.gz | rtf | HTML]
Baird, L. C. (1995). "Residual Algorithms: Reinforcement Learning with Function Approximation". Machine Learning: Proceedings of the Twelfth International Conference, 9-12 July, Morgan Kaufman Publishers, San Francisco, CA.(22 Nov 95 errata corrects errors in the published version).
[8 pages: pdf | ps.gz | rtf | HTML]
Baird, L. C. (1995). "Residual Algorithms". Proceedings of the Workshop on Value Function Approximation, Machine Learning Conference, July 9, (Technical report CMU-CS-95-206).(Workshop proceedings are at http://www.cs.cmu.edu/~reinf/ml95/proceedings.html).
[8 pages: pdf | paper.ps.gz | slides.ps.gz]
Harmon, M. E., & Baird, L. C. (1995). "Residual Advantage Learning Applied to a Differential Game". Proceedings of the International Conference on Neural Networks, Washington D.C, 3-6 June.
[6 pages: ps.gz | pdf | rtf]
Weaver, S. E., Baird, L. C., & Polycarpou, M. M. (1995). "On the Localization of Feedforward Networks". Proceedings of the American Control Conference.
[2 pages: ps.gz | pdf | LaTeX.tar.gz | HTML]
Harmon, M. E., Baird, L. C., & Klopf, A. H. (1995). "Advantage Updating Applied to a Differential Game". Advances in Neural Information Processing Systems 7.
[10 pages: ps.gz | pdf | rtf | HTML]
Baird, L. C. (1994). "Reinforcement Learning in Continuous Time: Advantage Updating". Proceedings of the International Conference on Neural Networks, Orlando, FL, June.
[8 pages: ps.gz | pdf | rtf | HTML]
Williams, R. J., & Baird, L. C. (1994). "Tight Performance Bounds on Greedy Policies Based on Imperfect Value Functions". Proceedings of the Tenth Yale Workshop on Adaptive and Learning Systems, Yale University, June 1994.
[6 pages: ps.gz | pdf | LaTeX | HTML]
Baird, L. C. (1993). Advantage Updating. (Technical Report WL-TR-93-1146). Wright-Patterson Air Force Base Ohio: Wright Laboratory. (Available from the Defense Technical Information Center, Cameron Station, Alexandria, VA 22304-6145)).
[48 pages: pdf | ps.gz | rtf | HTML | C code]
Baird, L. C., & Klopf, A. H. (1993). Reinforcement Learning with High-Dimensional, Continuous Actions. (Technical Report WL-TR-93-1147). Wright-Patterson Air Force Base Ohio: Wright Laboratory. (Available from the Defense Technical Information Center, Cameron Station, Alexandria, VA 22304-6145).
[19 pages: ps.gz | pdf | rtf | HTML]
Williams, R. J., & Baird, L. C. (1993). Analysis of Some Incremental Variants of Policy Iteration: First Steps Toward Understanding Actor-Critic Learning Systems. (Technical Report NU-CCS-93-11). Northeastern University.
[49 pages: ps.gz | pdf]
Williams, R. J., & Baird, L. C. (1993). Tight Performance Bounds on Greedy Policies Based on Imperfect Value Functions. (Technical Report NU-CCS-93-14). Northeastern University.
[20 pages: ps.gz | pdf | LaTeX | HTML]
Baird, L. C. (1992). "Function Minimization for Dynamic Programming Using Connectionist Networks". Proceedings of the IEEE Conference On Systems, Man, and Cybernetics, Chicago, IL.
[6 pages: ps.gz | pdf | rtf | HTML]
Williams, R. J., & Baird, L. C. (1990). "A Mathematical Analysis of Actor-Critic Architectures for Learning Optimal Controls Through Incremental Dynamic Programming". Proceedings of the Sixth Yale Workshop on Adaptive and Learning Systems, Yale University, 15-17 August.
[6 pages: ps.gz | pdf | LaTeX | HTML]
Baird, L. C., & Wang, P. S. (1995). 3-D object perception using gradient descent. The Journal of Mathematical Imaging and Vision. 5(2).
Baird, L. C., & Klopf, A. H. (1994). Reinforcement learning and optimal decision making. Journal of Mathematical Psychology. 38(3).(Invited book review of Rosenstein, G.,1991, Income and choice in biological control systems: A framework for understanding the function and dysfunction of the brain).
Baird, L. C., & Klopf, A. H. (1993). A hierarchical network of provably optimal learning control systems: Extensions of the associative control process (ACP) network. Adaptive Behavior. 1(3).
Baird, L. C., & Klopf, A. H. (1993). "Extensions of the associative control process (ACP) network: Hierarchies and provable optimality". Proceedings of the Second International Conference on Simulation of Adaptive Behavior, Honolulu, Hawaii.
Baker, W. L., Atkins, S. C., Baird, L. C., Koenig, M. A., Millington, P. J., & Nistler, N. F. (1993). Investigation of Drive-Reinforcement Learning and Application of Learning to Flight Control. (Technical Report WL-TR-93-1153). Charles Stark Draper Laboratory, Cambridge, MA.
Baird, L. C., & Wang, P. S. (1991). "3D object recognition using gradient descent and the universal 3D ray grammar". Proceedings of SPIE Conference on Intelligent Robots and Computer Vision X: Algorithms and Techniques, Boston, MA, vol. 1607.
Alexander, J. S., Baird, L. C., Baker, W. L., & Farrell, J. A. (1991). "A design and simulation tool for connectionist learning control systems: Application to autonomous underwater vehicles". Proceedings of the Society for Computer Simulation Conference Baltimore, MD.
Baird, L. C. (1991). Learning and adaptive hybrid systems for nonlinear control. (Technical Report CSDL-T-1099). Charles Stark Draper Laboratory, Cambridge, MA. (Master's thesis, College of Computer Science, Northeastern University Boston).
Baird, L. C., & Baker, W. L. (1990). "A connectionist learning system for nonlinear control". Proceedings of the AIAA Conference on Guidance, Navigation, and Control, Portland, Oregon.