Refereed Journal/Conference/Symposium/Workshop Publications

• Prashant Doshi, Piotr Gmytrasiewicz, A Particle Filtering Based Approach to Approximating Interactive POMDPs, In Proceedings of the Twentieth National Conference on AI (AAAI), pp. 969-974, Pittsburg, July 9-13, 2005.

• Prashant Doshi, Piotr Gmytrasiewicz, Approximating State Estimation in Multiagent Settings using Particle Filters, In Proceedings of the Fourth International Autonomous Agents and Multiagent Systems Conference (AAMAS), Utrecht, Netherlands, July 25-29, 2005.

• Piotr Gmytrasiewicz, Prashant Doshi, A Framework for Sequential Planning in Multiagent Settings, Journal of AI Research (JAIR). Vol 24:1-31, 2005.

• Prashant Doshi, Richard Goodwin, Rama Akkiraju, Kunal Verma, Dynamic Workflow Composition using Markov Decision Processes, International Journal of Web Services Research (JWSR), Vol. 2(1):1-17, 2005.

• Rama Akkiraju, John Colgrave, Kunal Verma, Richard Goodwin, Prashant Doshi, Juhnyoung Lee, Dynamic Discovery and Binding of Web Services to Abstract Web Process Flows, Invited submission to the Journal of Web Services Research (JWSR). Under Review. Oct 2004.

• 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.

• Piotr Gmytrasiewicz, Prashant Doshi, A Framework for Sequential Planning in Multi-agent Settings, In Proceedings of the Sixth 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

• Piotr Gmytrasiewicz, Prashant Doshi, Interactive POMDPs: Properties and Preliminary Results, In Proceedings of the Third International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), Poster, pp. 1374-1375, New York City, NY, July 19-23, 2004.

• Prashant Doshi, Richard Goodwin, Rama Akkiraju, Kunal Verma, Dynamic Workflow Composition using Markov Decision Processes, In Proceedings of the Second International Conference on Web Services (ICWS), pp. 576-582, San Diego, CA, July 6-9, 2004.

• Kunal Verma, Rama Akkiraju, Richard Goodwin, Prashant Doshi, Juhnyoung Lee, On Accommodating Inter-Service Dependencies in Web Process Flow Composition, In Working Notes of the Spring Symposium on Semantic Web Services, AAAI, pp., Stanford, California, Mar 22-24, 2004.

• 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.

• 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.

• Rama Akkiraju, Richard Goodwin, Prashant Doshi, Sascha Roeder, A Method For Semantically Enhancing the Service Discovery Capabilities of UDDI, In Proceedings of the Workshop on Information Integration on the Web, IJCAI 2003, pp., Acapulco, Mexico, Aug 9-10, 2003.

• Prashant Doshi, Lloyd Greenwald, John Clarke, Using Bayesian Networks for Cleansing Trauma Data , In Proceedings of the Sixteenth International FLAIRS Conference, pp. 72-76, St. Augustine, Fl., May 12-14, 2003.

• 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.

• John Clarke, Stanley Trooskin, Prashant Doshi, Lloyd Greenwald, Charles Mode, Time to Laparotomy for Intra-Abdominal Bleeding does affect Survival for Delays upto 90 minutes, In the Journal of Trauma: Injury, Infection, and Critical Care(AAST), Vol 52(3):420-425, 2002.

• 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.

• Piotr Gmytrasiewicz, Prashant Doshi, A Framework for Sequential Planning in Multiagent Settings, Technical Report, UIC-AIL-TR05, AI Lab, Univ. of Illinois at Chicago, Chicago, IL 60607.

• Prashant Doshi, Richard Goodwin, Rama Akkiraju, Sascha Roeder, Parameterized Semantic Matchmaking for Workflow Composition, Technical Report, RC23133, IBM Research, T.J. Watson Research Center, NY. Winner of the IBM Research eBusiness Summer Intern poster competition, 2002

• 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.