Shapiro, D., Value-Driven Agents, Ph.D. thesis, Stanford
University, Department of Management Science and Engineering, 2001. [Abstract | Full Text]
Books and Journals, edited
Shapiro, D., and Goker, M. (eds.), AI Magazine Special Issue on Advancing AI Research and Applications by Learning from What Went Wrong and Why. AAAI Press, Summer 2008.
Remagnino, P., and Shapiro, D. (eds.), Computational Intelligence: Special Issue on Artificial Intelligence Methods for Ambient Intelligence Volume 23 Issue 4, November 2007.
Ramos, C., Augusto, J., and Shapiro, D. (eds.). IEEE Intelligent Systems Special Issue on Ambient Intelligence, Vol. 23, No. 2. Mar./Apr. 2008.
Augusto, J., and Shapiro, D. (eds.), Advances
in Ambient Intelligence. (2007). IOS press. ISBN 978-1-58603-800-7
Journal Articles
Konik, T., OÕRorke,
P., and Shapiro, D. Skill Transfer
through Goal-Driven Representation Mapping. Cognitive Systems
Research, Special Issue on Analogies - Integrating Cognitive Abilities,
Vol. 10, No. 3, September 2009. PDF
Ichise,
R., Shapiro, D., Langley, P. (2004). Structured
program induction from behavioral traces, IEICE Transactions on Information and Systems,
Vol. J87-D-1, No. 6, pp. 730-740 (in Japanese). The Institute
of Electronics, Information and Communication Engineers.
Tong,
R., & Shapiro, D., Experimental Investigations of uncertainty in a
rule-based system for information retrieval, International Journal of Man Machine Studies
22, 265-282, 1985. (Invited
paper.)
McCune,
B., Tong, R., Dean, J., & Shapiro, D., RUBRIC: A system for rule-based
information retrieval, IEEE Transactions on Software Engineering, vol
SE-11, no 9, September 1985, pp 939-945. Also in Readings in Information Systems, Sparck-Jones,
K., & Willett, P. (eds), Morgan Kaufmann
Publishers, Inc., May 1997.
Editorials
Shapiro, D., and Goker, M. (2008). What Went Wrong and Why: Lessons from AI Research and Development. AI Magazine Special Issue on Advancing AI Research and Applications by Learning from What Went Wrong and Why. AAAI Press, Summer 2008.
Ramos, C., Augusto, J., and Shapiro, D. (2008). Ambient Intelligence - The Next Step for Artificial Intelligence. In Ramos, C., Augusto, J., and Shapiro, D. (eds.). IEEE Intelligent Systems Special Issue on Ambient Intelligence, Vol. 23, No. 2. Mar./Apr. 2008
Remagnino, P., and Shapiro, D. (2007). Artificial Intelligence Methods for Ambient Intelligence, in Computational Intelligence: Special Issue on Artificial Intelligence Methods for Ambient Intelligence, Volume 23, Issue 4, November 2007, pp 393-394.
Conference
Articles
Konik, K., Ali, K., Shapiro, D., Li, N., and Stracuzzi, D. Improving Structural Knowledge Transfer with Parametric Adaptation (2010). The 23rd Florida Artificial Intelligence Research Society Conference (FLAIRS-23), Daytona Beach, Florida. (In press.)
Li, N., Stracuzzi, D., Cleveland,
G., Konik, T., Nejati, N.,
Shapiro, D., Molineaux, M., and Aha, D. (2009). Constructing Game Agents from Video of Human
Behavior, Proceedings of the Fifth AAAI Conference on Artificial
Intelligence and Interactive Digital Entertainment (AIIDE), Stanford, CA. PDF
Ali, K., Leung, K., Konik,
K., Choi, D., and Shapiro, D. (2009). Knowledge-Directed Theory Revision, Nineteenth
International Conference on Inductive Logic Programming, Leuven, Belgium
Shapiro,
D., Konik, K., and OÕRorke,
P. (2008). Achieving
Far Transfer in an Integrated Cognitive Architecture, Proceedings of the
Twenty-third Conference of the Association for the Advancement of Artificial
Intelligence, Chicago, IL. PDF
Billman,D., Shapiro, D., &
Cummings, K. (2005) Processes in Diagnostic Reasoning: Information Use in Causal
Explanations. In Program of the Twenty-Seventh Annual
Conference of the Cognitive Science Society. pp.
262-267, Erlbaum: Hillsdale, NJ. PDF
Langley,
P., Cummings, K., & Shapiro, D. (2004). Hierarchical
skills and cognitive architectures. Proceedings of
the Twenty-Sixth Annual Conference of the Cognitive Science Society.
Chicago, IL. PDF
Choi, D., Kaufman,
M., Langley, P., Nejati, N., & Shapiro, D.
(2004). An
architecture for persistent reactive behavior. Proceedings of
the Third International Joint Conference on Autonomous Agents and Multi Agent
Systems. New York: ACM Press. PDF
Shapiro,
D., & Langley, P. (2002). Separating skills
from preference: using learning to program by reward. Nineteenth
International Conference on Machine Learning. PDF
Bay,
S., Shapiro, D., & Langley, P.
(2002). Revising
engineering models: combining computational discovery with knowledge. European Conference on Machine Learning. PDF
Ichise,
R., Shapiro, D., & Langley, P.
(2002). Learning
hierarchical skills from observation.
Proceedings of the Fifth International Conference on
Discovery Science. PDF
Ichise,
R., Shapiro, D., & Langley, P.
(2002). Learning programs
from observations of other agents.
Proceedings of the Joint Agent Workshop (JAWS2002),
pp. 1-8, in Japanese.
Shapiro,
D., Langley, P., & Shachter, R. (2001). Using background
knowledge to speed reinforcement learning, Fifth International Conference
on Autonomous Agents. PDF
Shapiro,
D., & Langley, P. (1999). Controlling physical agents through reactive logic programming. Third International Conference on Autonomous Agents (pp. 386-387).
Seattle: ACM. PDF
Shapiro,
D. (1997). Giving
up for no good reason. Nineteenth Annual Conference of
the Cognitive Science Society, Stanford CA.
Cromarty,
A., Shapiro, D., & Fehling, M. (1984). Still planners run deep: shallow reasoning for fast
replanning. Proceedings of the
Society of Photo-Optical Engineers, Technical Symposium East. SPIE.
Shapiro,
D., & McCune, B. (1983). The intelligent program editor: a knowledge-based system for supporting
program and documentation maintenance. Proceedings of the Trends and Applications Conference:
Automating Intelligent Behavior; Applications and Frontiers, pp 226-232. Gaithersburg, MD. IEEE.
Shapiro,
D., Dean, J., & McCune, B. (1984). A knowledge base for supporting an
intelligent program editor.
Proceedings of the Seventh International Conference on Software
Engineering, pp. 381-386. Orlando, FL. IEEE.
McCune,
B., Tong, R.,
Dean, J., & Shapiro, D. (1983). RUBRIC: a system for rule-based information
retrieval. Proceedings of the Seventh International
Computer Software and Applications Conference, pp 166-172. IEEE Computer
Society.
Tong, R., Shapiro, D., McCune, B., & Dean, J. (1983). A rule-based approach to information
retrieval: some results and comments. Proceedings of the
National Conference on Artificial Intelligence, pp 411-415. William
Kauffman.
Tong, R., & Shapiro, D. (1983). An experiment
with multiple-valued logics in an expert system. Proceedings of the
IFAC Symposium on Fuzzy Information, Knowledge Representation and Decision
Analysis. Marseille, France.
Tong, R., Shapiro, D., Dean, J., & McCune, B. (1983). A comparison of
uncertainty calculi in an expert system for information retrieval. Proceedings of the Eigth International
Joint Conference on Artificial Intelligence, pp 194-197. Karlsruhe,
Germany. William Kauffman.
Refereed Workshop
Papers
Langley, P., Arai, S., & Shapiro, D. (2004). Model-Based Learning with Hierarchical Relational
Skills, International Conference on Machine Learning, Workshop on
Relational Reinforcement Learning.
Shapiro,
D., and Collopy, P. (2004). Communicating Values to Autonomous Agents,
Stanford Spring Symposium on Interaction between Humans and Autonomous Systems
over Extended Operation. Stanford,
CA. PDF
Shapiro,
D., & Gervasio, M. (2003). Adaptive interfaces for value-driven agents. Stanford Spring
Symposium, Workshop on Human Interaction with Autonomous Systems in Complex
Environments, Stanford University, Stanford, CA. PDF
Shapiro,
D., & Shachter, R. (2002). User-agent value alignment. Stanford Spring Symposium, Workshop on Safe Agent Learning.
Stanford University, Stanford, CA.
PDF
Shapiro,
D. (1999). Controlling
gaming agents via reactive programs, Stanford Spring Symposium Workshop on
Artificial Intelligence and Computer Games. PDF
Schoppers, M., &
Shapiro, D. (1997).
Designing embedded agents to optimize end-user objectives. Proceedings of the Fourth International Workshop on Agent Theories,
Architectures and Languages.
Providence, RI. Reprinted in Intelligent Agents, v.4, Springer Verlag. PDF
Tong, R., Applebaum, L., &
Shapiro, D. (1986).
A general purpose inference engine for evidential reasoning
research. Proceedings of the Second Workshop on
Uncertainty in Artificial Intelligence, American Association of Artificial
Intelligence.
Non-Refereed
Workshop Papers
Langley, P., Shapiro, D., Aycinena,
M., & Siliski, M. (2003). A value-driven
architecture for intelligent behavior. Proceedings
of the IJCAI-2003 Workshop on Cognitive Modeling of Agents and Multi-Agent
Interactions. Acapulco, Mexico. PDF
Shapiro,
D. (1989). The
astronaut and the banana peel. Proceedings NASA/JPL
Workshop on Space Telerobotics, Pasadena, CA.
Technical Reports
Langley,
P., Choi, D., & Shapiro, D. (2004). A
cognitive architecture for physical agents. Institute for the Study
of Learning and Expertise, Palo Alto, CA. PDF
Fehling,
M., & Shapiro D., A systems level perspective on IVHS design, University of
California Institute of Transportation Studies, Richmond Field Station, Bldg
452, 1357 S. 46th St., Richmond, CA 94804-4698, California PATH Reports to
Caltrans 96-C10, 6/96.
Shapiro,
D., Extra
Vehicular Activity Retriever simulation video (Parts 1 and II), Image
Sciences Division, NASA Johnson Space Center, Houston TX 77058, wo 55033.005, 3/93.
Shapiro, D., Architectures for semi-autonomous planning,
NASA Lyndon Johnson Space Center, NAS 9-18162, 7/91.
Shapiro, D., A principled design for the operations management
application onboard Space Station Freedom, Final Report, NASA Lyndon
Johnson Space Center, Houston TX 77058, NAS 9-18083, 8/89.
Schoppers, M., & Shapiro, D., Telerobotic control of teams
of semi-autonomous agents, U.S. Army Tank-Automotive Command, Warren, MI
48397-5000, DAAE07-88-C-R076, 4/89.
Shapiro, D., Shu, R., & Tollander, C., An Operations Monitoring Assistant, U.S. Army
Communications-Electronics Command, Fort Monmouth, NJ 07703, DAAB07-86-C0051,
11/88.
Shapiro, D., An Extra Vehicular Activity Retriever scenario,
NASA Lyndon Johnson Space Center, Houston TX 77058, Technical report JSC-23196,
9/88.
Shapiro,
D., & Tollander, C., The battlefield commanderÕs assistant
project, Army Communications-Electronics Command, DAAB07-84-K516, 1/87.
Stachnic, G., Applebaum, L., Marks, P.,
Marsh, J., Rosenschein, J., Schoppers,
M., & Shapiro, D., Airland battle management planning study, Defense
Advanced Research Projects Agency, 1400 Wilson Boulevard, Arlington, VA
22209-2308, DAAH01-86-C-0487, 10/86.
Shapiro, D., Finger, J., Courand,
G., McCune, B., & Payne, R., The design of TEMPLAR (a Tactical Expert Mission
Planner), Rome Air Development Center, Rome NY, RADC-TR-84-134, 1984.
McCune,
B., Dean, J., Tong, R., & Shapiro, D., RUBRIC, a system for rule based information
retrieval, Advanced Information and Decision Systems, 1500 Plymouth St,
Mountain View CA, TR-1018-1, 2/83.
McCune,
B., Dean, J., Shapiro, D., & Tong, R., Rule-based information retrieval, Intelligence
Applications of Advanced Computer and Information Technology: Focus on Artificial Intelligence,
Office of Research and Development, Central Intelligence Agency, Washington, DC,
11/82.
Shapiro,
D., McCune, B., & Wilson, G., Design of an intelligent program editor, Office
of Naval Research, 800 N. Quincy St, Arlington, VA 22217, N00014-82-C-0119,
9/82.
Shapiro,
D., & McCune, B., Searching a knowledge base of programs and documentation, Air Force
Office of Scientific Research, Bolling Air Force
Base, D.C. 20332, F49620-81-C-0067, 5/82.
Manuscripts
Shapiro,
D., Shachter, R., and Langley, P. User-Agent Value Alignment. (Long
version) PDF
Shapiro, D., Billman, D., Marker,
M., and Langley, P.
A Human-Centered Approach to Monitoring Complex Dynamic Systems.
PDF