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On the one hand, the definition of accurate action models for planning is still a bottleneck. On the other hand, off-the-shelf planners fail to scale-up and to provide good solutions in many domains. In these problematic domains, planners can exploit domain-specific control knowledge to improve their performance in terms of both speed and quality of the solutions. However, manual definition of control knowledge is quite difficult. This paper reviews recent techniques in machine learning for the automatic definition of planning knowledge. It has been organized according to the target of the learning process: automatic definition of planning action models and automatic definition of planning control knowledge. In addition, the paper reviews the advances in the related field of reinforcement learning.<\/jats:p>","DOI":"10.1017\/s026988891200001x","type":"journal-article","created":{"date-parts":[[2012,11,12]],"date-time":"2012-11-12T06:28:35Z","timestamp":1352701715000},"page":"433-467","source":"Crossref","is-referenced-by-count":68,"title":["A review of machine learning for automated planning"],"prefix":"10.48130","volume":"27","author":[{"given":"Sergio","family":"Jim\u00e9nez","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tom\u00e1s","family":"De La Rosa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Susana","family":"Fern\u00e1ndez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fernando","family":"Fern\u00e1ndez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Borrajo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"27968","published-online":{"date-parts":[[2012,11,12]]},"reference":[{"key":"S026988891200001X_ref148","first-page":"73","article-title":"Learning-assisted automated planning: looking back, taking stock, going forward","volume":"24","author":"Zimmerman","year":"2003","journal-title":"AI Magazine"},{"key":"S026988891200001X_ref55","unstructured":"Garc\u00eda-Dur\u00e1n R. , Fern\u00e1ndez F. , Borrajo D. 2006. 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In International Joint Conference on Artificial Intelligence, Hyderabad, India."},{"key":"S026988891200001X_ref141","unstructured":"Yoon S. , Fern A. , Givan R. 2006. Learning heuristic functions from relaxed plans. In International Conference on Automated Planning and Scheduling (ICAPS-2006), Cumbria, UK."},{"key":"S026988891200001X_ref138","unstructured":"Xu Y. , Fern A. , Yoon S. W. 2007. Discriminative learning of beam-search heuristics for planning. In International Joint Conference on Artificial Intelligence, Hyderabad, India."},{"key":"S026988891200001X_ref24","doi-asserted-by":"crossref","unstructured":"Bylander T. 1991. Complexity results for planning. 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In International Joint Conference on Artificial Intelligence, IJCAI-89, Detroit, Michigan, USA, 675\u2013680."},{"key":"S026988891200001X_ref111","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-68856-3"},{"key":"S026988891200001X_ref66","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1613\/jair.855","article-title":"The FF planning system: fast plan generation through heuristic search","volume":"14","author":"Hoffmann","year":"2001","journal-title":"Journal of Artificial Intelligence Research"},{"key":"S026988891200001X_ref118","unstructured":"Sanner S. , Boutilier C. 2006. Practical linear value-approximation techniques for first-order MDPs. In Proceedings of the 22nd Conference in Uncertainty in Artificial Intelligence, Cambridge, MA, USA."},{"key":"S026988891200001X_ref7","unstructured":"Benson S. S. 1997. Learning Action Models for Reactive Autonomous Agents. 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PhD thesis, King's College, Oxford."},{"key":"S026988891200001X_ref108","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1613\/jair.2113","article-title":"Learning symbolic models of stochastic domains","volume":"29","author":"Pasula","year":"2007","journal-title":"Journal of Artificial Intelligence Research"},{"key":"S026988891200001X_ref145","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1613\/jair.1880","article-title":"The first probabilistic track of the international planning competition","volume":"24","author":"Younes","year":"2005","journal-title":"Journal of Artificial Intelligence Research"},{"key":"S026988891200001X_ref105","volume-title":"Shakey the Robot","author":"Nilsson","year":"1984"},{"key":"S026988891200001X_ref64","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2008.10.013"},{"key":"S026988891200001X_ref103","unstructured":"Nayak P. , Kurien J. , Dorais G. , Millar W. , Rajan K. , Kanefsky R. 1999. Validating the DS-1 remote agent experiment. In Artificial Intelligence, Robotics and Automation in Space."},{"key":"S026988891200001X_ref101","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1613\/jair.1141","article-title":"SHOP2: an HTN planning system","volume":"20","author":"Nau","year":"2003","journal-title":"Journal of Artificial Intelligence Research"},{"key":"S026988891200001X_ref46","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(93)90080-U"},{"key":"S026988891200001X_ref60","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2008.10.012"},{"key":"S026988891200001X_ref125","volume-title":"Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)","author":"Sutton","year":"1998"},{"key":"S026988891200001X_ref40","unstructured":"Driessens K. , Ramon J. 2003. Relational instance based regression for relational reinforcement learning. In International Conference on Machine Learning, Washington, DC, USA."},{"key":"S026988891200001X_ref29","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1613\/jair.2077","article-title":"Marvin: a heuristic search planner with online macro-action learning","volume":"28","author":"Coles","year":"2007","journal-title":"Journal of Artificial Intelligence Research"},{"key":"S026988891200001X_ref39","doi-asserted-by":"publisher","DOI":"10.1023\/B:MACH.0000039779.47329.3a"},{"key":"S026988891200001X_ref119","volume-title":"Proceedings of the 24th AAAI Conference on Artificial Intelligence (AAAI-10)","author":"Sanner","year":"2010"},{"key":"S026988891200001X_ref37","unstructured":"de la Rosa T. , Jim\u00e9nez S. , Borrajo D. 2008. Learning relational decision trees for guiding heuristic planning. In International Conference on Automated Planning and Scheduling (ICAPS 08), Sydney, Australia."},{"key":"S026988891200001X_ref30","unstructured":"Cortellessa G. , Cesta A. 2006. Evaluating mixed-initiative systems: an experimental approach. In Proceedings of the 16th International Conference on Automated Planning & Scheduling, ICAPS-06, Cumbria, UK."},{"key":"S026988891200001X_ref53","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1613\/jair.1129","article-title":"PDDL2.1: an extension to PDDL for expressing temporal planning domains","author":"Fox","year":"2003","journal-title":"Journal of Artificial Intelligence Research"},{"key":"S026988891200001X_ref8","unstructured":"Bergmann R. , Wilke W. 1996. PARIS: flexible plan adaptation by abstraction and refinement. In Workshop on Adaptation in Case-Based Reasoning, ECAI-96."},{"key":"S026988891200001X_ref17","unstructured":"Botea A. , M\u00fcller M. , Schaeffer J. 2007. Fast planning with iterative macros. In Proceedings of the International Joint Conference on Artificial Intelligence IJCAI-07, 1828\u20131833."},{"key":"S026988891200001X_ref28","doi-asserted-by":"crossref","unstructured":"Cohen W. W. 1990. Learning approximate control rules of high utility. In International Conference on Machine Learning, Austin, Texas, USA.","DOI":"10.1016\/B978-1-55860-141-3.50036-5"},{"key":"S026988891200001X_ref33","first-page":"726","volume-title":"Proceedings of the 20th International Joint Conference on Artificial Intelligence","author":"Croonenborghs","year":"2007"},{"key":"S026988891200001X_ref26","unstructured":"Castillo L. , Fdez-Olivares J. , Garc\u00eda-P\u00e9rez O. , Palao F. 2006. Bringing users and planning technology together. Experiences in SIADEX. In International Conference on Automated Planning and Scheduling (ICAPS 2006), Cumbria, UK."},{"key":"S026988891200001X_ref31","doi-asserted-by":"crossref","unstructured":"Cresswell S. , McCluskey T. L. , West M. 2009. Acquisition of object-centred domain models from planning examples. In Proceedings of the 19th International Conference on Automated Planning and Scheduling (ICAPS-09), Thessaloniki, Greece.","DOI":"10.1609\/icaps.v19i1.13391"},{"key":"S026988891200001X_ref27","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(93)90060-O"},{"key":"S026988891200001X_ref25","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(94)90081-7"},{"key":"S026988891200001X_ref51","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(71)90010-5"},{"key":"S026988891200001X_ref115","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-006-5833-1"},{"key":"S026988891200001X_ref97","unstructured":"Mour\u00e3o K. , Petrick R. P. A. , Steedman M. 2010. Learning action effects in partially observable domains. In European Conference on Artificial Intelligence, Barcelona, Spain."},{"key":"S026988891200001X_ref112","unstructured":"Ramirez M. , Geffner H. 2009. Plan recognition as planning. In IJCAI'09: Proceedings of the 21st International Jont Conference on Artifical Intelligence, Pasadena, CA, USA."},{"key":"S026988891200001X_ref1","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(02)00246-1"},{"key":"S026988891200001X_ref48","unstructured":"Fern A. , Yoon S. , Givan R. 2004. Learning domain-specific control knowledge from random walks. In International Conference on Automated Planning and Scheduling, Whistler, Canada, 191\u2013199."},{"key":"S026988891200001X_ref127","unstructured":"Theocharous G. , Kaelbling L. P. 2003. Approximate planning in POMDPs with macro-actions. In Proceedings of Advances in Neural Information Processing Systems 16, Whistler, Canada."},{"key":"S026988891200001X_ref91","unstructured":"McGann C. , Py F. , Rajan K. , Ryan J. , Henthorn R. 2008. Adaptive control for autonomous underwater vehicles. In National Conference on Artificial Intelligence (AAAI'2008), Chicago, Illinois, USA."},{"key":"S026988891200001X_ref6","volume-title":"Dynamic Programming and Modern Control Theory","author":"Bellman","year":"1965"},{"key":"S026988891200001X_ref98","doi-asserted-by":"crossref","unstructured":"Muggleton S. 1995. Stochastic logic programs. In International Workshop on Inductive Logic Programming, Leuven, Belguim.","DOI":"10.1016\/B978-1-55860-335-6.50052-0"},{"key":"S026988891200001X_ref61","volume-title":"Automated Planning Theory and Practice","author":"Ghallab","year":"2004"},{"key":"S026988891200001X_ref102","unstructured":"Nau D. S. , Smith S. J. , Erol K. 1998. Control strategies in htn planning: theory versus practice. In In AAAI-98\/IAAI-98 Proceedings, Madison, Wisconsin. USA."},{"key":"S026988891200001X_ref82","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(99)00060-0"},{"key":"S026988891200001X_ref124","unstructured":"Strehl A. L. , Littman M. L. 2005. 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Improving control-knowledge acquisition for planning by active learning. In European Conference on Learning, Berlin, Germany, 138\u2013149."},{"key":"S026988891200001X_ref126","doi-asserted-by":"crossref","unstructured":"Taylor M. E. , Stone P. 2007. Cross-domain transfer for reinforcement learning. In International Conference on Machine Learning, ICML, Corvallis, OR, USA.","DOI":"10.1145\/1273496.1273607"},{"key":"S026988891200001X_ref19","unstructured":"Boutilier C. , Reiter R. , Price B. 2001. Symbolic dynamic programming for first-order MDPs. In International Joint Conference on Artificial Intelligence, Seattle, Washington, USA."},{"key":"S026988891200001X_ref3","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(99)00071-5"},{"key":"S026988891200001X_ref11","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(98)00034-4"},{"key":"S026988891200001X_ref77","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1613\/jair.301","article-title":"Reinforcement learning: a survey","volume":"4","author":"Kaelbling","year":"1996","journal-title":"Journal of Artificial Intelligence Research"},{"key":"S026988891200001X_ref16","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1613\/jair.1696","article-title":"Macro-FF: improving AI planning with automatically learned macro-operators","volume":"24","author":"Botea","year":"2005","journal-title":"Journal of Artificial Intelligence Research"},{"key":"S026988891200001X_ref18","unstructured":"Botea A. , M\u00fcller M. , Schaeffer J. 2005b. Learning partial-order macros from solutions. In ICAPS 2005. Proceedings of the 15th International Conference on Automated Planning and Scheduling, Biundo, S., Myers, K. & Rajan, K. (eds). Monterey, California, 231\u2013240."},{"key":"S026988891200001X_ref20","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-540-73263-1","volume-title":"Metalearning: Applications to Data Mining\u2014Cognitive Technologies","author":"Brazdil","year":"2009"},{"key":"S026988891200001X_ref76","unstructured":"Jim\u00e9nez S. , Fern\u00e1ndez F. , Borrajo D. 2008. The PELA architecture: integrating planning and learning to improve execution. In Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI-08), Chicago, IL, USA."},{"key":"S026988891200001X_ref47","first-page":"70","volume-title":"International Conference on Artificial Intelligence Planning Systems, AIPS96","author":"Ferguson","year":"1996"},{"key":"S026988891200001X_ref35","unstructured":"Dawson C. , Silklossly L. 1977. The role of preprocessing in problem solving system. In International Joint Conference on Artificial Intelligence, IJCAI-77, Cambridge, MA, USA, 465\u2013471."},{"key":"S026988891200001X_ref49","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1613\/jair.1700","article-title":"Approximate policy iteration with a policy language bias: solving relational Markov decision processes","volume":"25","author":"Fern","year":"2006","journal-title":"Journal of Artificial Intelligence Research"},{"key":"S026988891200001X_ref113","doi-asserted-by":"crossref","unstructured":"Ramirez M. , Geffner H. 2010. Probabilistic plan recognition using off-the-shelf classical planners. In National Conference on Artificial Intelligence (AAAI'2010), Atlanta, Georgia, USA.","DOI":"10.1609\/aaai.v24i1.7745"},{"key":"S026988891200001X_ref52","unstructured":"Florez J. E. , Garca J. , Torralba A. , Linares C. , Garca-Olaya A. , Borrajo D. 2010. Timiplan: an application to solve multimodal transportation problems. In Proceedings of SPARK, Scheduling and Planning Applications woRKshop, ICAPS'10, Toronto, Canada."},{"key":"S026988891200001X_ref13","first-page":"1636","article-title":"Fast planning through planning graph analysis","volume":"90","author":"Blum","year":"1995","journal-title":"Artificial Intelligence"},{"key":"S026988891200001X_ref23","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1613\/jair.1789","article-title":"Learning in real-time search: a unifying framework","volume":"25","author":"Bulitko","year":"2006","journal-title":"Journal of Artificial Intelligence Research"},{"key":"S026988891200001X_ref96","unstructured":"Mour\u00e3o K. , Petrick R. P. A. , Steedman M. 2008. Using kernel perceptrons to learn action effects for planning. In Proceedings of the International Conference on Cognitive Systems (CogSys 2008), Karlsruhe, Germany."},{"key":"S026988891200001X_ref56","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-010-0194-6"},{"key":"S026988891200001X_ref10","volume-title":"Neuro-Dynamic Programming (Optimization and Neural Computation Series, 3)","author":"Bertsekas","year":"1996"},{"key":"S026988891200001X_ref137","doi-asserted-by":"crossref","unstructured":"Winner E. , Veloso M. 2003. DISTILL: towards learning domain-specific planners by example. In International Conference on Machine Learning, ICML'03, Washington, DC, USA.","DOI":"10.21236\/ADA461131"},{"key":"S026988891200001X_ref57","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008134010576"},{"key":"S026988891200001X_ref134","unstructured":"Wang X. 1994. Learning planning operators by observation and practice. In International Conference on AI Planning Systems, AIPS-94, Chicago, Illinois, USA."},{"key":"S026988891200001X_ref75","unstructured":"Lanchas J. , Jim\u00e9nez S. , Fern\u00e1ndez F. , Borrajo D. 2007. Learning action durations from executions. In Working notes of the ICAPS'07 Workshop on AI Planning and Learning, Rhode Island, Providence, USA."},{"key":"S026988891200001X_ref59","doi-asserted-by":"crossref","unstructured":"Gerevini A. , Saetti A. , Vallati M. 2009a. An automatically configurable portfolio-based planner with macro-actions: PbP. In Proceedings of the 19th International Conference on Automated Planning and Scheduling (ICAPS-09), Thessaloniki, Greece.","DOI":"10.1609\/icaps.v19i1.13386"},{"key":"S026988891200001X_ref110","unstructured":"Quinlan J. , Cameron-Jones R. 1995. Introduction of logic programs: FOIL and related systems. New Generation Computing, Special issue on Inductive Logic Programming 13(3\u20134), 287\u2013312."},{"key":"S026988891200001X_ref62","unstructured":"Gil Y. 1992. Acquiring Domain Knowledge for Planning by Experimentation. PhD thesis, School of Computer Science, Carnegie Mellon University, Pittsburgh."},{"key":"S026988891200001X_ref78","volume-title":"Senior Member Track of the AAAI","author":"Kambhampati","year":"2007"},{"key":"S026988891200001X_ref63","unstructured":"Gretton C. , Thi\u00e9baux S. 2004. Exploiting first-order regression in inductive policy selection. In Conference on Uncertainty in Artificial Intelligence, Banff, Canada."},{"key":"S026988891200001X_ref83","unstructured":"Kittler J. 1998. Combining classifiers: A theoretical framework. Pattern Analysis and Application 1(1), 18\u201327."},{"key":"S026988891200001X_ref88","unstructured":"Martin M. , Geffner H. 2000. Learning generalized policies in planning using concept languages. In International Conference on Artificial Intelligence Planning Systems, AIPS00, Breckenridge, USA."},{"key":"S026988891200001X_ref107","volume-title":"The Logic of Adaptive Behavior: Knowledge Representation and Algorithms for Adaptive Sequential Decision Making under Uncertainty in First-Order and Relational Domains","author":"Otterlo","year":"2009"},{"key":"S026988891200001X_ref65","unstructured":"Hern\u00e1ndez C. , Meseguer P. 2007. Improving LRTA*(k). In International Joint Conference on Artificial Intelligence, IJCAI-07, Hyderabad, India, 2312\u20132317."},{"key":"S026988891200001X_ref95","volume-title":"Machine Learning","author":"Mitchell","year":"1997"},{"key":"S026988891200001X_ref50","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(72)90051-3"},{"key":"S026988891200001X_ref32","unstructured":"Croonenborghs T. , Driessens K. , Bruynooghe M. 2007a. Learning relational options for inductive transfer in relational reinforcement learning. In Proceedings of the 17th Conference on Inductive Logic Programming, Corvallis, OR, USA."},{"key":"S026988891200001X_ref117","unstructured":"Sanner S. , Boutilier C. 2005. Approximate linear programming for first-order mdps. In Proceedings of the 21st Conference on Uncertainty in Artificial Intelligence, Edinburgh, Scotland, UK, 509\u2013517."},{"key":"S026988891200001X_ref67","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1613\/jair.855","article-title":"The FF planning system: fast plan generation through heuristic search","volume":"14","author":"Hoffmann","year":"2001","journal-title":"Journal of Artificial Intelligence Research"},{"key":"S026988891200001X_ref120","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2010.07.007"},{"key":"S026988891200001X_ref72","first-page":"131","volume-title":"Proceedings of the 6th International Conference on AI Planning and Scheduling","author":"Ilghami","year":"2002"},{"key":"S026988891200001X_ref43","volume-title":"GPS: A Case Study in Generality and Problem Solving, ACM Monograph Series","author":"Ernst","year":"1969"},{"key":"S026988891200001X_ref74","unstructured":"Jaeger M. 1997. Relational bayesian networks. In Conference on Uncertainty in Artificial Intelligence, Rhode Island, Providence, USA."},{"key":"S026988891200001X_ref45","first-page":"115","volume-title":"In New Directions in AI Planning","author":"Estlin","year":"1996"},{"key":"S026988891200001X_ref68","unstructured":"Hogg C. , Kuter U. , Mu\u00f1oz-Avila H. 2009. Learning hierarchical task networks for nondeterministic planning domains. In International Joint Conference on Artificial Intelligence, IJCAI-09, Pasadena, CA, USA."},{"key":"S026988891200001X_ref73","unstructured":"Ilghami O. , Nau D. S. , Mu\u00f1oz-Avila H. 2006. Learning to do HTN planning. 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In Conference on Innovative Applications of Artificial Intelligence, IAAI-99, Orlando, Florida, USA."},{"key":"S026988891200001X_ref81","unstructured":"Kersting K. , Raedt L. D. 2001. Towards combining inductive logic programming with Bayesian networks. In International Conference on Inductive Logic Programming, Strasbourg, France, 118\u2013131."},{"key":"S026988891200001X_ref128","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2005.05.004"},{"key":"S026988891200001X_ref99","doi-asserted-by":"crossref","unstructured":"Muise C. , McIlraith S. , Baier J. A. , Reimer M. 2009. Exploiting N-gram analysis to predict operator sequences. In 19th International Conference on Automated Planning and Scheduling (ICAPS), Thessaloniki, Greece.","DOI":"10.1609\/icaps.v19i1.13392"},{"key":"S026988891200001X_ref4","unstructured":"Barto A. , Duff M. 1994. Monte carlo matrix inversion and reinforcement learning. Advances in Neural Information Processing Systems 6, 687\u2013694."},{"key":"S026988891200001X_ref85","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(90)90054-4"},{"key":"S026988891200001X_ref104","unstructured":"Newton M. A. H. , Levine J. , Fox M. , Long D. 2007. Learning macro-actions for arbitrary planners and domains. In International Conference on Automated Planning and Scheduling, Providence, USA."},{"key":"S026988891200001X_ref114","unstructured":"Reynolds S. I. 2002. Reinforcement Learning with Exploration. PhD thesis, The University of Birmingham, UK."},{"key":"S026988891200001X_ref58","doi-asserted-by":"crossref","unstructured":"Gartner T. , Driessens K. , Ramon J. 2003. Graph kernels and Gaussian processes for relational reinforcement learning. 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In International Joint Conference on Artificial Intelligence, IJCAI-07, Hyderabad, India.","DOI":"10.1613\/jair.2489"},{"key":"S026988891200001X_ref146","unstructured":"Zelle J. , Mooney R. 1993. Combining FOIL and EBG to speed-up logic programs. In International Joint Conference on Artificial Intelligence. IJCAI-93, Chamb\u00e9ry, France."},{"key":"S026988891200001X_ref94","volume-title":"Machine Learning: An Artificial Intelligence Approach","author":"Mitchell","year":"1982"},{"key":"S026988891200001X_ref130","first-page":"207","volume-title":"Proceedings of the DARPA Workshop on Innovative Approaches to Planning, Scheduling, and Control","author":"Veloso","year":"1990"},{"key":"S026988891200001X_ref139","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2006.11.005"},{"key":"S026988891200001X_ref80","unstructured":"Keller R. 1987. The Role of Explicit Contextual Knowledge in Learning Concepts to Improve Performance. PhD thesis, Rutgers University."},{"key":"S026988891200001X_ref2","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1613\/jair.2575","article-title":"Learning partially observable deterministic action models","volume":"33","author":"Amir","year":"2008","journal-title":"Journal of Artificial Intelligence Research"},{"key":"S026988891200001X_ref9","volume-title":"Dynamic Programming and Optimal Control","author":"Bertsekas","year":"1995"},{"key":"S026988891200001X_ref106","unstructured":"Oates T. , Cohen P. R. 1996. Searching for planning operators with context-dependent and probabilistic effects. In National Conference on Artificial Intelligence, Portland, Oregon, USA."},{"key":"S026988891200001X_ref21","unstructured":"Bresina J. L. , Jansson A. K. , Morris P. H. , Rajan K. 2005. Mixed-initiative activity planning for mars rovers. In IJCAI, Edinburgh, Scotland, UK, 1709\u20131710."},{"key":"S026988891200001X_ref71","doi-asserted-by":"crossref","unstructured":"Ilghami O. , Mu\u00f1oz-Avila H. , Nau D. S. , Aha D. W. 2005. Learning approximate preconditions for methods in hierarchical plans. In International Conference on Machine Learning, Bonn, Germany.","DOI":"10.1145\/1102351.1102394"},{"key":"S026988891200001X_ref70","doi-asserted-by":"crossref","unstructured":"Howe A. E. , Dahlman E. , Hansen C. , Scheetz M. , Mayrhauser A. V. 1999. Exploiting competitive planner performance. In Proceedings of the 5th European Conference on Planning, Durham, UK.","DOI":"10.1007\/10720246_5"},{"key":"S026988891200001X_ref44","first-page":"223","article-title":"On the complexity of domain-independent planning","volume":"56","author":"Erol","year":"1992","journal-title":"Artificial Intelligence"},{"key":"S026988891200001X_ref14","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(01)00108-4"},{"key":"S026988891200001X_ref123","unstructured":"Srivastava S. , Immerman N. , Zilberstein S. 2008. Learning generalized plans using abstract counting. In National Conference on Artificial Intelligence (AAAI'2008), Chicago, Illinois, USA."},{"key":"S026988891200001X_ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-017-2053-3_14"},{"key":"S026988891200001X_ref84","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(85)90012-8"},{"key":"S026988891200001X_ref69","unstructured":"Hogg C. , Mu\u00f1oz-Avila H. , Kuter U. 2008. 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PhD thesis, University of Amsterdam IDSIA, the Netherlands."},{"key":"S026988891200001X_ref93","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4613-1703-6"},{"key":"S026988891200001X_ref86","doi-asserted-by":"publisher","DOI":"10.1207\/s15516709cog1201_3"},{"key":"S026988891200001X_ref38","unstructured":"de la Rosa T. , Jim\u00e9nez S. , Garc\u00eda-Dur\u00e1n R. , Fern\u00e1ndez F. , Garc\u00eda-Olaya A. , Borrajo D. 2009. Three relational learning approaches for lookahead heuristic planning. 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