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Refereed Journal/Conference/Symposium/Workshop
Publications |
Referred Journal and Conference Papers
Refereed Symposium and Workshop Papers
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Prashant Doshi, A Framework for Optimal Sequential
Planning in Multiagent Settings, In Proceedings of the Ninth
AAAI/SIGART Doctoral Consortium, AAAI, pp. 985-986, San Jose, CA, July
25-26, 2004.
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Piotr Gmytrasiewicz, Prashant Doshi, A Framework for Sequential
Planning in Multiagent Settings. AI&M 9-2004. In Proceedings of the
Eight International Symposium on Artificial Intelligence and Mathematics,
Fort Lauderdale, Florida, Jan 4-6, 2004.
Piotr Gmytrasiewicz, Prashant Doshi, A Framework for Sequential
Planning in Multi-agent Settings, In Proceedings of the
Sixth International Workshop on Game Theory and Decision Theory, pp. 39-47,
New York City, NY, July 20, 2004.
Prashant Doshi, Piotr Gmytrasiewicz, A Particle Filtering Algorithm for
Interactive POMDPs, In Proceedings of the Workshop on Modeling
Other Agents from Observations, AAMAS, pp. 87-93, New York City, NY, July
19, 2004.
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Prashant Doshi, Piotr Gmytrasiewicz, Towards Affect-based
Approximations to Rational Planning: A Decision-Theoretic Perspective to
Emotions, In Working Notes of the Spring Symposium on Architectures
for Modeling Emotion: Cross-Disciplinary Foundations, AAAI, pp.,
Stanford, California, Mar 22-24, 2004.
Prashant Doshi, Lloyd Greenwald, John Clarke, Towards Effective Structure Learning
for Large Bayesian Networks, In Proceedings of the Workshop on
Probabilistic Approaches in Search, Eighteenth National Conference on
Artificial Intelligence, pp. 16-22, Edmonton, Canada, July 28
2002.
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Prashant Doshi, Lloyd Greenwald, John Clarke, On Retaining Intermediate Probabilistic
Models When Building Bayesian Networks, In Working Notes of
the Fall Symposium on Using Uncertainty Within Computation, AAAI, pp. 47-48, North Falmouth,
Mass., Nov 2-4, 2001.
Technical Reports (Unrefereed)
Theses and Related Documents
Prashant Doshi, Optimal Sequential
Planning in Partially Observable Multiagent Settings, Ph.D. Thesis
Proposal, Univ. of Illinois at Chicago, IL., June 2004.
Prashant Doshi, Effective Methods for Building
Probabilistic Models from Large Noisy Data Sets, Masters Thesis, Drexel University, Philadelphia, PA., June 2001.
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