1. The Science and Systems of Learning
    
2. Setting a Research Agenda on Educational Technology
    
3. Information Processing in Biological and Artificial Intelligent Systems
    
4. New Horizons in Biosystems Analysis and Control: Analysis, Control and Adaptation of Dynamical Systems in Biology,
    
5. Reinforcement Learning

The Science and Systems of Learning

Augmenting Our Ability to Learn and Create,
September 17-19, 1995.
URL: http://hi-c.eecs.umich.edu/papers/Science_Systems_Learning.pdf

This workshop was convened by a special cross-directorate committee of the NSF, the Committee on Collaborative Research Initiative on Learning and Intelligent Systems.
The participants were researchers and educators with backgrounds in the cognitive and social sciences, neuroscience, engineering, computer science, and education. The workshop report provides an overview on research in learning and intelligent systems from a cross-disciplinary perspective that could lead to new ways of learning-- in school, at home, and in the workplace--in the coming age of information. The report also includes illustrative examples of research domains that require collaborative efforts by researchers from several disciplines.

Setting a Research Agenda on Educational Technology
September 29-October 1, 1995
URL: http://www.cc.gatech.edu/gvu/edtech/nsfws/

The objective of this workshop was to focus on ways in which intelligent systems could be useful in all facets of education, including informal and self-directed learning. The workshop report provides examples of interdisciplinary research and systems development related to learning and cognitive functioning that range from empirical research to theory development to classroom practice and that address the application of advanced technologies and new understanding of cognition to the learning process.

Information Processing in Biological and Artificial Intelligent Systems
April 8-10, 1996.
URL: http://www-hbp.usc.edu/HBP/presentations/NSF-NISE.Workshop96/

This workshop brought together neuroscientists, physicists, mathematicians, and researchers in AI, control theory, and bioengineering to discuss research opportunities in modeling and understanding of information processing in biological systems, including the brain, for the benefit of studying biological systems and applying such knowledge to artificial intelligent systems. (Publication NSF 97-4)

New Horizons in Biosystems Analysis and Control: Analysis, Control and Adaptation of Dynamical Systems in Biology
November 13-15, 1995.
URL: http://robotics.eecs.berkeley.edu/~sastry

The participants in this workshop were from neuroscience, ecosystems, engineering, and computer science. They were brought together to discuss opportunities for collaborative research. The topics included systems identification and analysis tools designed to understand how biological systems interpret sensory signals, control physiological processes, and adaptively monitor and control bioprocesses. The objective was to bring together tools in biology and engineering and identify real-time, nonlinear, stochastic systems capable of learning.

Reinforcement Learning
April 12-14, 1996
URL: http://www.csee.usf.edu/~mahadeva/nsf-workshop/homepage.html

This workshop focused on interdisciplinary research in the area of reinforcement learning. Reinforcement learning is a phenomenon long observed in animals, including humans, that depends on feedback during learning. Reinforcement learning algorithms have been modeled computationally, and the models are being actively studied by an eclectic mix of scientists doing research in machine learning and neural nets, operations research, mathematics, psychology, robotics and engineering.
Thirty leading scientists from these fields met to discuss research and applications of reinforcement learning as used for adaptive control and learning in autonomous agents.