| Year |
Citation |
Score |
| 2020 |
Zhuo HH, Zha Y, Kambhampati S, Tian X. Discovering Underlying Plans Based on Shallow Models Acm Transactions On Intelligent Systems and Technology. 11: 1-30. DOI: 10.1145/3368270 |
0.5 |
|
| 2020 |
Sengupta S, Chowdhary A, Sabur A, Alshamrani A, Huang D, Kambhampati S. A Survey of Moving Target Defenses for Network Security Ieee Communications Surveys and Tutorials. 22: 1909-1941. DOI: 10.1109/Comst.2020.2982955 |
0.327 |
|
| 2017 |
Zhuo HH, Kambhampati S. Model-lite planning: Case-based vs. model-based approaches Artificial Intelligence. 246: 1-21. DOI: 10.1016/J.Artint.2017.01.004 |
0.461 |
|
| 2017 |
Nguyen T, Sreedharan S, Kambhampati S. Robust planning with incomplete domain models Artificial Intelligence. 245: 134-161. DOI: 10.1016/J.Artint.2016.12.003 |
0.512 |
|
| 2016 |
De S, Hu Y, Meduri VV, Chen Y, Kambhampati S. BayesWipe: A Scalable Probabilistic Framework for Improving Data Quality Journal of Data and Information Quality. 8: 5. DOI: 10.1145/2992787 |
0.681 |
|
| 2015 |
Balakrishnan R, Kambhampati S. Click efficiency: a unified optimal ranking for online Ads and documents Journal of Intelligent Information Systems. DOI: 10.1007/s10844-015-0366-3 |
0.468 |
|
| 2015 |
Zhang Y, Sreedharan S, Kambhampati S. Capability models and their applications in planning Proceedings of the International Joint Conference On Autonomous Agents and Multiagent Systems, Aamas. 2: 1151-1159. |
0.339 |
|
| 2014 |
Li N, Cushing W, Kambhampati S, Yoon S. Learning probabilistic hierarchical task networks as probabilistic context-free grammars to capture user preferences Acm Transactions On Intelligent Systems and Technology. 5. DOI: 10.1145/2589481 |
0.795 |
|
| 2014 |
Talamadupula K, Kambhampati S. Easychair as a pedagogical tool engaging graduate students in the reviewing process Proceedings of the National Conference On Artificial Intelligence. 4: 3052-3053. |
0.711 |
|
| 2014 |
Nguyen TA, Kambhampati S. A heuristic approach to planning with incomplete STRIPS action models Proceedings International Conference On Automated Planning and Scheduling, Icaps. 2014: 181-189. |
0.418 |
|
| 2013 |
Balakrishnan R, Kambhampati S, Jha M. Assessing relevance and trust of the deep web sources and results based on inter-source agreement Acm Transactions On the Web. 7. DOI: 10.1145/2460383.2460390 |
0.556 |
|
| 2013 |
Hu Y, Talamadupula K, Kambhampati S. Dude, srsly?: The surprisingly formal nature of Twitter's language Proceedings of the 7th International Conference On Weblogs and Social Media, Icwsm 2013. 244-253. |
0.717 |
|
| 2013 |
Zhuo HH, Kambhampati S. Action-model acquisition from noisy plan traces Ijcai International Joint Conference On Artificial Intelligence. 2444-2450. |
0.415 |
|
| 2013 |
Zhuo HH, Nguyen T, Kambhampati S. Refining incomplete planning domain models through plan traces Ijcai International Joint Conference On Artificial Intelligence. 2451-2457. |
0.383 |
|
| 2013 |
Zhuo HH, Nguyen T, Kambhampati S. Model-lite case-based planning Proceedings of the 27th Aaai Conference On Artificial Intelligence, Aaai 2013. 1077-1083. |
0.302 |
|
| 2013 |
Nguyen TA, Kambhampati S, Do M. Synthesizing robust plans under incomplete domain models Advances in Neural Information Processing Systems. |
0.333 |
|
| 2013 |
Borrajo D, Fratini S, Kambhampati S, Oddi A. ICAPS 2013 - Proceedings of the 23rd International Conference on Automated Planning and Scheduling: Preface Icaps 2013 - Proceedings of the 23rd International Conference On Automated Planning and Scheduling. |
0.38 |
|
| 2012 |
Zhang XS, Shrestha B, Yoon S, Kambhampati S, Dibona P, Guo JK, McFarlane D, Hofmann MO, Whitebread K, Appling DS, Whitaker ET, Trewhitt EB, Ding L, Michaelis JR, McGuinness DL, et al. An ensemble architecture for learning complex problem-solving techniques from demonstration Acm Transactions On Intelligent Systems and Technology. 3. DOI: 10.1145/2337542.2337560 |
0.334 |
|
| 2012 |
Nguyen TA, Do M, Gerevini AE, Serina I, Srivastava B, Kambhampati S. Generating diverse plans to handle unknown and partially known user preferences Artificial Intelligence. 190: 1-31. DOI: 10.1016/J.Artint.2012.05.005 |
0.777 |
|
| 2012 |
Zhuo HH, Yang Q, Kambhampati S. Action-model based multi-agent plan recognition Advances in Neural Information Processing Systems. 1: 368-376. |
0.439 |
|
| 2011 |
Balakrishnan R, Kambhampati S. SourceRank: Relevance and trust assessment for deep web sources based on inter-source agreement Proceedings of the 20th International Conference On World Wide Web, Www 2011. 227-236. DOI: 10.1145/1963405.1963440 |
0.508 |
|
| 2011 |
Balakrishnan R, Kambhampati S. Factal: Integrating deep web based on trust and relevance Proceedings of the 20th International Conference Companion On World Wide Web, Www 2011. 181-184. DOI: 10.1145/1963192.1963284 |
0.474 |
|
| 2011 |
Bryce D, Cushing W, Kambhampati S. State agnostic planning graphs: Deterministic, non-deterministic, and probabilistic planning Artificial Intelligence. 175: 848-889. DOI: 10.1016/J.Artint.2010.12.002 |
0.808 |
|
| 2010 |
Talamadupula K, Benton J, Kambhampati S, Schermerhorn P, Scheutz M. Planning for human-robot teaming in open worlds Acm Transactions On Intelligent Systems and Technology. 1. DOI: 10.1145/1869397.1869403 |
0.783 |
|
| 2009 |
Benton J, Do M, Kambhampati S. Anytime heuristic search for partial satisfaction planning Artificial Intelligence. 173: 562-592. DOI: 10.1016/J.Artint.2008.11.010 |
0.749 |
|
| 2008 |
Van Den Briel MHL, Vossen T, Kambhampati S. Loosely coupled formulations for automated planning: An integer programming perspective Journal of Artificial Intelligence Research. 31: 217-257. DOI: 10.1613/Jair.2443 |
0.452 |
|
| 2008 |
Bryce D, Kambhampati S, Smith DE. Sequential Monte Carlo in reachability heuristics for probabilistic planning Artificial Intelligence. 172: 685-715. DOI: 10.1016/J.Artint.2007.10.018 |
0.559 |
|
| 2008 |
Yoon S, Benton J, Kambhampati S. An online learning method for improving over-subscription planning Icaps 2008 - Proceedings of the 18th International Conference On Automated Planning and Scheduling. 404-411. |
0.411 |
|
| 2007 |
Bryce D, Kambhampati S. A tutorial on planning graph - Based reachability heuristics Ai Magazine. 28: 47-83. DOI: 10.1609/Aimag.V28I1.2028 |
0.545 |
|
| 2007 |
Benton J, Van Den Briel M, Kambhampati S. A hybrid linear programming and relaxed plan heuristic for partial satisfaction planning problems Icaps 2007, 17th International Conference On Automated Planning and Scheduling. 34-41. |
0.42 |
|
| 2007 |
Yoon S, Kambhampati S. Hierarchical strategy learning with hybrid representations Aaai Workshop - Technical Report. 52-56. |
0.328 |
|
| 2007 |
Cushing W, Kambhampati S, Mausam, Weld DS. When is temporal planning really temporal? Ijcai International Joint Conference On Artificial Intelligence. 1852-1859. |
0.429 |
|
| 2007 |
Kambhampati S. Model-lite planning for the Web age masses: The challenges of planning with incomplete and evolving domain models Proceedings of the National Conference On Artificial Intelligence. 2: 1601-1604. |
0.349 |
|
| 2007 |
Cushing W, Kambhampati S, Talamadupula K, Mausam DSW. Evaluating temporal planning domains Icaps 2007, 17th International Conference On Automated Planning and Scheduling. 105-112. |
0.774 |
|
| 2006 |
Bryce D, Kambhampati S, Smith DE. Planning graph heuristics for belief space search Journal of Artificial Intelligence Research. 26: 35-99. DOI: 10.1613/Jair.1869 |
0.526 |
|
| 2006 |
Bryce D, Kambhampati S, Smith DE. Sequential Monte Carlo in probabilistic planning reachability heuristics Icaps 2006 - Proceedings, Sixteenth International Conference On Automated Planning and Scheduling. 2006: 233-242. |
0.473 |
|
| 2005 |
Van Den Briel MHL, Kambhampati S. Optiplan: Unifying IP-based and graph-based planning Journal of Artificial Intelligence Research. 24: 919-931. DOI: 10.1613/Jair.1698 |
0.43 |
|
| 2005 |
Zimmerman T, Kambhampati S. Using memory to transform search on the planning graph Journal of Artificial Intelligence Research. 23: 533-585. DOI: 10.1613/Jair.1477 |
0.8 |
|
| 2005 |
Nie Z, Kambhampati S, Nambiar U. Effectively mining and using coverage and overlap statistics for data integration Ieee Transactions On Knowledge and Data Engineering. 17: 638-651. DOI: 10.1109/Tkde.2005.76 |
0.562 |
|
| 2005 |
Van Den Briel M, Vossen T, Kambhampati S. Reviving integer programming approaches for AI planning: A branch-and-cut framework Icaps 2005 - Proceedings of the 15th International Conference On Automated Planning and Scheduling. 310-319. |
0.351 |
|
| 2005 |
Benton J, Do MB, Kambhampati S. Over-subscription planning with numeric goals Ijcai International Joint Conference On Artificial Intelligence. 1207-1213. |
0.712 |
|
| 2005 |
Nigenda RS, Kambhampati S. Planning graph heuristics for selecting objectives in over-subscription planning problems Icaps 2005 - Proceedings of the 15th International Conference On Automated Planning and Scheduling. 192-201. |
0.451 |
|
| 2005 |
Bryce D, Kambhampati S. Cost sensitive reachability heuristics for handling state uncertainty Proceedings of the 21st Conference On Uncertainty in Artificial Intelligence, Uai 2005. 60-68. |
0.392 |
|
| 2004 |
Bryce D, Kambhampati S, Smith DE. Planning in belief space with a labelled uncertainty graph Aaai Workshop - Technical Report. 1-6. |
0.451 |
|
| 2004 |
Nie Z, Kambhampati S. A frequency-based approach for mining coverage statistics in data integration Proceedings - International Conference On Data Engineering. 20: 387-398. |
0.524 |
|
| 2004 |
Bryce D, Kambhampati S. Heuristic guidance measures for conformant planning Proceedings of the 14th International Conference On Automated Planning and Scheduling, Icaps 2004. 365-374. |
0.404 |
|
| 2003 |
Nigenda RS, Kambhampati S. Alt Alt p: Online parallelization of plans with heuristic state search Journal of Artificial Intelligence Research. 19: 631-657. DOI: 10.1613/Jair.1168 |
0.582 |
|
| 2003 |
Do MB, Kambhampati S. Sapa: A multi-objective metric temporal planner Journal of Artificial Intelligence Research. 20: 155-194. DOI: 10.1613/Jair.1156 |
0.717 |
|
| 2003 |
Zimmerman T, Kambhampati S. Learning-assisted automated planning: Looking back, taking stock, going forward Ai Magazine. 24: 73-96. DOI: 10.1609/Aimag.V24I2.1705 |
0.739 |
|
| 2003 |
Nareyek A, Kambhampati S. Introduction to the Special Issue on Planning: Research Issues at the Intersection of Planning and Constraint Programming Constraints. 8: 335-338. DOI: 10.1023/A:1025848402714 |
0.482 |
|
| 2003 |
Sanchez Nigenda R, Kambhampati S. Parallelizing state space plans online Ijcai International Joint Conference On Artificial Intelligence. 1522-1523. |
0.706 |
|
| 2003 |
Zimmerman T, Kambhampati S. Using available memory to transform Graphplan's search Ijcai International Joint Conference On Artificial Intelligence. 1526-1527. |
0.377 |
|
| 2002 |
Nguyen X, Kambhampati S, Nigenda RS. Planning graph as the basis for deriving heuristics for plan synthesis by state space and CSP search Artificial Intelligence. 135: 73-123. DOI: 10.1016/S0004-3702(01)00158-8 |
0.558 |
|
| 2001 |
Srivastava B, Nguyen X, Kambhampati S, Do MB, Nambiar U, Nie Z, Nigenda R, Zimmerman T. AltAlt: Combining Graphplan and Heuristic State Search Ai Magazine. 22: 88-90. DOI: 10.1609/Aimag.V22I3.1579 |
0.807 |
|
| 2001 |
Do MB, Kambhampati S. Planning as constraint satisfaction: Solving the planning graph by compiling it into CSP Artificial Intelligence. 132: 151-182. DOI: 10.1016/S0004-3702(01)00128-X |
0.724 |
|
| 2001 |
Srivastava B, Kambhampati S, Do MB. Planning the project management way: Efficient planning by effective integration of causal and resource reasoning in RealPlan Artificial Intelligence. 131: 73-134. DOI: 10.1016/S0004-3702(01)00122-9 |
0.769 |
|
| 2001 |
Nie Z, Kambhampati S. Joint optimization of cost and coverage of query plans in data integration International Conference On Information and Knowledge Management, Proceedings. 223-230. |
0.65 |
|
| 2001 |
Nguyen X, Kambhampati S. Reviving partial order planning Ijcai International Joint Conference On Artificial Intelligence. 459-464. |
0.364 |
|
| 2000 |
Kambhampati S. Planning Graph as a (Dynamic) CSP: Exploiting EBL, DDB and other CSP Search Techniques in Graphlan Journal of Artificial Intelligence Research. 12: 1. DOI: 10.1613/Jair.655 |
0.44 |
|
| 2000 |
Srivastava B, Kambhampati S. Scaling up planning by teasing out resource scheduling Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). 1809: 172-186. DOI: 10.1007/10720246_14 |
0.666 |
|
| 1998 |
Srivastava B, Kambhampati S. Synthesizing customized planners from specifications Journal of Artificial Intelligence Research. 8: 93-128. DOI: 10.1613/Jair.428 |
0.573 |
|
| 1998 |
Kambhampati S. On the relations between intelligent backtracking and failure-driven explanation-based learning in constraint satisfaction and planning Artificial Intelligence. 105: 161-208. DOI: 10.1016/S0004-3702(98)00087-3 |
0.499 |
|
| 1997 |
Kambhampati S. Refinement planning as a unifying framework for plan synthesis Ai Magazine. 18: 67-97. DOI: 10.21918/Aimag.V18I2.1295 |
0.54 |
|
| 1997 |
Ihrig LH, Kambhampati S. Storing and indexing plan derivations through explanation-based analysis of retrieval failures Journal of Artificial Intelligence Research. 7: 161-198. DOI: 10.1613/Jair.424 |
0.491 |
|
| 1997 |
Kambhampati S, Parker E, Lambrecht E. Understanding and extending Graphplan Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1348: 260-272. DOI: 10.1007/3-540-63912-8_91 |
0.502 |
|
| 1997 |
Kambhampati S. Challenges in bridging plan synthesis paradigms Ijcai International Joint Conference On Artificial Intelligence. 1: 44-49. |
0.34 |
|
| 1996 |
Kambhampati S, Katukam S, Qu Y. Failure driven dynamic search control for partial order planners: An explanation based approach Artificial Intelligence. 88: 253-315. DOI: 10.1016/S0004-3702(96)00005-7 |
0.406 |
|
| 1996 |
Kambhampati S, Dana S N. On the nature and role of modal truth criteria in planning Artificial Intelligence. 82: 129-155. DOI: 10.1016/0004-3702(94)00095-6 |
0.466 |
|
| 1995 |
Kambhampati S. Al Planning: A Prospectus on Theory and Applications Acm Computing Surveys (Csur). 27: 334-336. DOI: 10.1145/212094.212118 |
0.579 |
|
| 1995 |
Kambhampati S. A comparative analysis of partial order planning and task reduction planning Intelligence\/Sigart Bulletin. 6: 16-25. DOI: 10.1145/202187.202192 |
0.535 |
|
| 1995 |
Kambhampati S, Knoblock CA, Yang Q. Planning as refinement search: a unified framework for evaluating design tradeoffs in partial-order planning Artificial Intelligence. 76: 167-238. DOI: 10.1016/0004-3702(94)00076-D |
0.522 |
|
| 1994 |
Kambhampati S. Multi-contributor causal structures for planning: a formalization and evaluation Artificial Intelligence. 69: 235-278. DOI: 10.1016/0004-3702(94)90083-3 |
0.522 |
|
| 1994 |
Kambhampati S, Kedar S. A unified framework for explanation-based generalization of partially ordered and partially instantiated plans Artificial Intelligence. 67: 29-70. DOI: 10.1016/0004-3702(94)90011-6 |
0.518 |
|
| 1993 |
Kambhampati S, Cutkosky MS, Lee SH, Tenenbaum JM. Integrating General Purpose Planners and Specialized Reasoners: Case Study of a Hybrid Planning Architecture Ieee Transactions On Systems, Man and Cybernetics. 23: 1503-1518. DOI: 10.1109/21.257750 |
0.393 |
|
| 1992 |
Kambhampati S, Hendler JA. A validation-structure-based theory of plan modification and reuse Artificial Intelligence. 55: 193-258. DOI: 10.1016/0004-3702(92)90056-4 |
0.512 |
|
| 1986 |
Kambhampati S, Davis LS. Multiresolution Path Planning for Mobile Robots Ieee Journal On Robotics and Automation. 2: 135-145. DOI: 10.1109/JRA.1986.1087051 |
0.342 |
|
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