Professor Leonard M. Uhr

Professor Uhr earned his Ph.D. from the University of Michigan in 1957, served several years on the faculty there, and moved to the University of Wisconsin faculty in 1965. As one of the initial members of the UW Computer Sciences Department (which had been established only a year prior to his joining), Professor Uhr was instrumental in initiating the Department's curriculum and research in artificial intelligence, and he was centrally influential in shaping their maturation and evolution over his entire 26 years as an active faculty member. He regularly taught both undergraduate and graduate courses, was a successful research scientist, and was a much-sought-after mentor of graduate students. He retired from teaching in 1992 but remained active in research and publishing.

Professor Uhr's research and writing focused on computer perception and learning, and on the use of parallel computer architectures for artificial intelligence in general and for computer vision in particular. He was quite expert in many aspects of human neurophysiology and perception, and a central theme of much of his research was to design computational structures and processes based on his understanding of how the human nervous system works. He was one of the early proponents of integration of symbolic artificial intelligence with methods for dealing with uncertainty.

On these topics, Professor Uhr published seven books (as author and/or editor) and nearly 150 journal and conference papers. His seminal work was perhaps an article written in 1963 with Charles Vossler, "A Pattern Recognition Program That Generates, Evaluates, and Adjusts Its Own Operators," reprinted in Computers and Thought -- edited by E. Feigenbaum and J. Feldman -- which showcases the work of the scientists who not only defined the field of artificial intelligence but who are responsible for having developed it into what it is today. He served as Ph.D. major professor for 20 students, many of whom have gone on to become in their own right important contributors to artificial intelligence research and related areas of computer science.

Professor Uhr was a true intellectual, an independent thinker, a scholar in love with ideas new and old, and a gentle man. His passion for developing new insights made knowledgeable use of and always manifested genuine respect for the thoughts and perspectives of others -- whether those of his students, his UW colleagues, or his colleagues and intellectual predecessors elsewhere.

Professor Uhr was born in 1927, and as a child, he attended the Oak Lane Country Day School outside of Philadelphia. He graduated from Princeton in 1949, with a B.A. in Psychology. He received masters degrees in Philosophy from the University of Brussels and Johns Hopkins University in 1951 before obtaining his Ph.D. in Psychology from the University of Michigan in 1957. Leonard Uhr was elected as a Fellow of the American Association for Artificial Intelligence in 1995 for his pioneering contributions to artificial intelligence, but out of modesty, declined the honor.

Leonard Uhr died on October 5, 2000 at his home in Madison. He was 73 years old. He is sorely missed by those who had the good fortune to have known him.

What follows is a brief record of Leonard Uhr's professional life:

Education
Ph.D., Psychology, University of Michigan, 1957.
M.A., Philosophy, Johns Hopkins Univ., 1951.
B.A., Psychology, Princeton Univ., 1949.

Professional Experience

Scientific Contributions

Books

  1. Honavar, V. & Uhr, L. (Ed.) Artificial Intelligence and Neural Networks: Steps Toward Principled Integration. New York: Academic Press. 1994.
  2. Uhr, L. Multi-Computer Architectures for Artificial Intelligence: Toward Fast, Robust, Parallel Systems. New York: Wiley. 1987.
  3. Uhr, L. (Ed.) Parallel Computer Vision. Boston: Academic Press. 1987.
  4. Uhr, L. Algorithmically Structured Computer Arrays and Networks: Architectures for Images, Percepts, Models, Information. Boston: Academic Press. 1984.
  5. Uhr, L. Pattern Recognition, Learning, and Thought. Englewood Cliffs: Prentice-Hall. 1973.
  6. Uhr, L. Pattern Recognition. (Ed.) New York: Wiley. 1966.
Noteworthy Research Articles (out of a total of over 150)
  1. Honavar, V. & Uhr, L. Integrating Symbol Processing and Connectionist Networks, and Beyond. Invited Paper In: Intelligent Hybrid Systems. Goonatilake, S. & Khebbal, S. (Ed.) London, Wiley: 1995.
  2. Uhr, L. Digital and Analog Subnet Structures for Connectionist Networks. In: Artificial Intelligence and Neural Networks: Steps Toward Principled Integration. Honavar, V. & Uhr, L. (ed.) Boston: Academic Press: 1994.
  3. Honavar, V. & Uhr, L. Generative Learning Structures and Processes for Connectionist Networks. Information Sciences 70 75-108. 1993.
  4. Uhr, L. Forms Structure Form at Ever ``Higher'' and ``Lower'' Levels. In: Arcelli, C., Cordella, L.P., Sanniti di Baja, G. (ed). Visual Form: Analysis and Recognition. New York: Plenum. 1991.
  5. Honavar, V. & Uhr, L. Coordination and Control Structures and Processes: Possibilities for Connectionist Networks. Journal of Experimental and Theoretical Artificial Intelligence 2 277-302. 1990.
  6. Uhr, L. Increasing the Power of Connectionist Networks, By Improving Structure, Processes, and Learning. Connection Science 2 179-193. 1990.
  7. Li, Z. N. & Uhr, L. Pyramid Vision Using Key Features to Integrate Image-Driven Bottom-Up and Model-Driven Top-Down Processes. IEEE Trans. Systems, Man, and Cybernetics 16 250-262. 1987.
  8. Li, Z.N. & Uhr, L. Evidential Reasoning in a Computer Vision System. In: Proceedings of the Second Annual Conference on Uncertainty in Artificial Intelligence. 1986.
  9. Uhr, L. Massively Parallel Hardware-Software Structures for Learning. In: Complex Systems - Operational Approaches to Neurobiology, Physics, and Computers. H. Haken (Ed.), pp. 212-224. Berlin: Springer-Verlag. 1985.
  10. Uhr, L. & Schmitt, L. The Several Steps from Icon to Symbol Using Structured Cone/Pyramids. In: Multi-Resolution Systems for Image Processing. A. Rosenfeld (Ed.), pp. 86-100. Amsterdam: North-Holland. 1984.
  11. Uhr, L. Comparing Serial Computers, Arrays, and Networks Using Measures of ``Active Resources''. IEEE Transactions on Computers 31(10): 1022-1025. 1982
  12. Uhr, L. & Douglass, R. A Parallel-Serial Recognition Cone System for Perception: Some Test Results. Pattern Recogition 11(1): 29-39. 1979.
  13. Uhr, L. Parallel-Serial Production Systems With Many Working Memories. In: Proc. IJCAI., Japan, 1979.
  14. Uhr, L. & Kochen, M. Toward a Greater Generality in Artificial Intelligence. In: Proc. ECAI, pp. 351-354. Hamburg, Germany, 1978.
  15. Uhr, L. & Kochen, M. Toward Adaptive (Computer-Based) Hospital Care Systems That Can Grow and Improve as a Result of User Participation. International Journal of Biomedical Computing, 10 191-203, 1979.
  16. Uhr, L. Tryouts Toward the Production of Thought. In: Perception & Cognition: Issues in the Foundations of Psychology. Minnesota Studies in the Philosophy of Science. C.W. Savage (Ed). pp. 327-364. 1978.
  17. Uhr, L. Toward Integrated Cognitive Systems, Which Must Make Fuzzy Decisions About Fuzzy Problems. In: Fuzzy Sets. L. Zadeh et al. (Ed.), pp. 353-393. New York: Academic Press, 1975.
  18. Uhr, L. DECIDER-1, A System That Chooses Among Different Types of Acts. In: Proc. 3rd IJCAI, Palo Alto, 1973.
  19. Uhr, L. Flexible Syntactic Pattern Recognition. Pattern Recognition 3, 363-384, 1971.
  20. Uhr, L. Layered Recognition Cone Networks That Preprocess, Classify, and Describe. IEEE Trans. on Computers, 21, 758-768, 1972.
  21. Uhr, L. & Jordan, M. The Learning of Parameters for Generating Compound Characterizers for Pattern Recognition. In: Proc. IJCAI, Washington, 1969.
  22. Uhr, L. & Kochen, M. MIKROKOSMS and Robots. In: Proc. IJCAI, Washington, 1969.
  23. Uhr, L. Pattern-String Learning Programs, Behavioural Science 9, 258-270.
  24. Uhr, L. Pattern Recognition Computers as Models for Perception, Psychogical Bulletin 60 40-73, 1963.
  25. Uhr, L. & Vossler, C. A Pattern Recognition Program That Generates, Evaluates, and Adjusts its Own Operators. In: Computers and Thought, E. Feigenbaum & J. Feldman (Ed.), New York: McGraw-Hill. 1963.

Selected Professional Activities

Leonard Uhr's Research Contributions

Len Uhr was one of the earliest researchers in the field of Artificial Intelligence. His contributions to the field span over 3 decades, on topics as diverse as pattern recognition, machine learning, perception- mediated reasoning and action, computer vision, neural networks, and parallel and distributed architectures for AI.

Len was among the pioneers who worked on synthesis of computer programs for tasks where neither the shape (form) nor the size (complexity) of the solution can be specified a-priori. His paper with Vossler on programs that generate, evaluate and adjust their own operators for pattern recognition (published in 1963 in the volume "Computers and Thought", edited by Feigenbaum and Feldman) is an example of such work that anticipated much current research on automated program synthesis, constructive induction, constructive neural network learning algorithms.

Len's work with Kochen on simulation of agents published in the 1969 IJCAI foreshadowed current research in Intelligent Agents. He was among the first to propose parallel production system models for perception, inference, and action in his 1971 IJCAI paper. This was followed by more than a decade of significant research on various aspects of massively parallel computer architectures and algorithms (including brain-like networks of simple processors or connectionist networks - long before they became fashionable) for computer vision, and perception-mediated reasoning and action.

Around 1986, Len's attention started to shift back to learning. Between 1986 and 1992, Len and his students developed some of the first approaches to generative or constructive learning algorithms for pattern recognition aimed to address some of the limitations of connectionist learning models that relied entirely on parameter modification.

Between 1992 and 1996, Len occupied himself with several foundational problems in AI, including the design of general, robust, and flexible adaptive architectures for embodied intelligence and integration of symbolic and connectionist approaches to AI and cognitive modelling. During the past few years, Len focused his attention to societal and educational impact of information technologies such as the Internet and the World-Wide Web. He became very interested in developing tools for improving access to information, bridging the gap between information haves and have nots in the digital age, using information technologies to improve democracy, and related societal issues. Most of his thoughts on this topic are available only in the form of the notes that he kept and recollections of those who had conversations with him. It is hoped that these records will be made available to a larger audience in a suitable form in the near future.

Len founded the AI program at University of Wisconsin-Madison. The UW-Madison AI group has produced a number of Ph.D.s who have gone on to make significant contributions in artificial intelligence, computer science, and even the arts, in academia as well as the industry. As a professor, Len has, over the years, nurtured, fostered, and mentored a large and diverse reservoir of talent in AI. The depth and breadth of his knowledge in not only AI but also the related fields of psychology, philosophy, and neuroscience, and his single-minded dedication to scientific research and teaching has been truly inspiring to his many graduate students.

Ph.D. Dissertations Completed Under Leonard Uhr's Supervision

  1. Timmreck, Eric M.
    Advising by Computers: Course Advising, Medical Treatment, General Advising
    July 3, 1968

  2. Fabens, William J. H.
    An Adaptive Interactive Teaching System for Programming Languages
    August 13, 1970

  3. Towster, Edwin
    Several Methods of Concept-Formation by Computer
    December 12, 1969

  4. Wexler, Jonathan D.
    A Generative, Remedial and Query System for Teaching by Computer
    March 21, 1970

  5. Zobrist, Albert L.
    Extraction and Representation of Features for Pattern Recognition and the Game of GO
    August 10, 1970

  6. Naylor, William Clark
    Some Studies in Interactive Machine Imitation Using Character Recognition
    February 23, 1971

  7. Jordan, Sara R.
    Learning to Use Contextual Patterns in Language Processing
    September 7, 1971

  8. Krueger, Myron William
    Computer Controlled Responsive Environments
    July 22, 1974

  9. Williams, Harold A.
    A Net-Structure Learning System for Pattern Description
    December 12, 1973

  10. LeFaivre, Richard
    Fuzzy Problem-Solving
    August 7, 1974

  11. Potter, Jerry
    Motion Extraction and Utilization in Scene Description
    September 18, 1975

  12. Douglass, Robert J.
    A Computer Vision Model for Recognition, Description, and Depth Perception in Outdoor Scenes
    January 6, 1978

  13. Korn, Robert K.
    Machine Learning During Continuous Interaction With A Simulated Environment
    December 19, 1977

  14. Orgren, Paul J.
    The Induction of the Syntax of Natural Language by Computer
    December 7, 1979

  15. Schmitt, Lorenz A.
    A Structured Approach to Computer Image Understanding; The Use and Representation of Real-World Knowledge in an Artificial Vision System
    June 21, 1982

  16. Li, Ze-Nian
    Pyramid Vision Using Key Features and Evidential Reasoning
    July 14, 1986

  17. Sandon, Peter
    Learning Object-Centered Representations
    July 30, 1987

  18. Ho, Seng-Beng
    Representing and Using Functional Definitions for Visual Recognition
    December 10, 1987

  19. Honavar, Vasant
    Generative Learning Structures for Generalized Connectionist Networks
    August 14, 1990

  20. Mani, Ganesh
    Learning Language about Objects and Using This Language to Learn Further: The Childlike System August 9, 1993

  21. Zeidenberg, Matt To be completed.

Professor Leonard Uhr's Obituary from the Wisconsin State Journal


This page is maintained in memory of Professor Leonard Uhr by:

Dr. Vasant Honavar
Director, Artificial Intelligence Research Laboratory
Department of Computer Science
Iowa State University
Atanasoff Hall, Ames, IA 50011-1040 USA
phone: +1-515-294-4377, fax: +1-515-294-0258