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Specifying a complete domain model is time-consuming, which has been a bottleneck of AI planning technique application in many real-world scenarios.
Learning by observation and practice: A framework for automatic acquisition of planning operators
Xuemei Wang · 1994
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An integrated approach of learning, planning, and execution
Ramón García-Martínez and Daniel Borrajo · 2000
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Planning as heuristic search
Blai Bonet and Hector Geffner · 2001
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The FF planning system: Fast plan generation through heuristic search
Jörg Hoffmann and Bernhard Nebel · 2001
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Symbolic pattern databases in heuristic search planning
Stefan Edelkamp · 2002
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Learning probabilistic relational planning rules
Hanna Pasula, Luke S. Zettlemoyer, and Leslie Pack Kaelbling · 2004
Earlier work this paper cites.
Learning symbolic models of stochastic domains
Hanna M. Pasula, Luke S. Zettlemoyer, and Leslie Pack Kaelbling · 2007
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Learning action models from plan examples using weighted MAX-SAT
Qiang Yang, Kangheng Wu, and Yunfei Jiang · 2007
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Transferring knowledge from another domain for learning action models
Hankui Zhuo, Qiang Yang, Derek Hao Hu, and Lei Li · 2008
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Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio · 2010
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Learning action effects in partially observable domains
Kira Mourão, Ronald P. A. Petrick, and Mark Steedman · 2010
Earlier work this paper cites.
Learning complex action models with quantifiers and logical implications
Hankz Hankui Zhuo, Qiang Yang, Derek Hao Hu, and Lei Li · 2010
Cited alongside, same era.
Generalised domain model acquisition from action traces
Stephen Cresswell and Peter Gregory · 2011
Cited alongside, same era.
Learning action models for multi-agent planning
Hankz Hankui Zhuo, Hector Muñoz-Avila, and Qiang Yang · 2011
Cited alongside, same era.
Cross-domain action-model acquisition for planning via web search
Hankz Hankui Zhuo, Qiang Yang, Rong Pan, and Lei Li · 2011
Cited alongside, same era.
Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto García-Durán, Jason Weston, and Oksana Yakhnenko · 2013
Cited alongside, same era.
Acquiring planning domain models using LOCM
Stephen Cresswell, Thomas Leo McCluskey, and Margaret Mary West · 2013
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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Crowdsourced action-model acquisition for planning
Hankz Hankui Zhuo · 2015
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Domain model acquisition in domains with action costs
Peter Gregory and Alan Lindsay · 2016
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Learning relational dynamics of stochastic domains for planning
David Martínez, Guillem Alenyà, Carme Torras, Tony Ribeiro, and Katsumi Inoue · 2016
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Purely declarative action descriptions are overrated: Classical planning with simulators
Guillem Francès, Miquel Ramírez, Nir Lipovetzky, and Hector Geffner · 2017
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Efficient, safe, and probably approximately complete learning of action models
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Cited alongside, same era.
Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
Cited alongside, same era.
Action-model acquisition from noisy plan traces
Hankz Hankui Zhuo and Subbarao Kambhampati · 2013
Cited alongside, same era.
A review on multi-label learning algorithms
Min-Ling Zhang and Zhi-Hua Zhou · 2014
Cited alongside, same era.
Action-model acquisition for planning via transfer learning
Hankz Hankui Zhuo and Qiang Yang · 2014
Cited alongside, same era.
Learning hierarchical task network domains from partially observed plan traces
Hankz Hankui Zhuo, Héctor Muñoz-Avila, and Qiang Yang · 2014
Cited alongside, same era.
Roni Stern and Brendan Juba · 2017
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Learning STRIPS action models with classical planning
Diego Aineto, Sergio Jiménez, and Eva Onaindia · 2018
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A review of learning planning action models
Ankuj Arora, Humbert Fiorino, Damien Pellier, Marc Métivier, and Sylvie Pesty · 2018
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Classical planning in deep latent space: Bridging the subsymbolic-symbolic boundary
Masataro Asai and Alex Fukunaga · 2018
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Relational inductive biases, deep learning, and graph networks
Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinícius Flores Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, Çaglar Gülçehre, Francis Song, Andrew J. Ballard, Justin Gilmer, George E. Dahl, Ashish Vaswani, Kelsey Allen, Charles Nash, Victoria Langston, Chris Dyer, Nicolas Heess, Daan Wierstra, Pushmeet Kohli, Matthew Botvinick, Oriol Vinyals, Yujia Li, and Razvan Pascanu · 2018
Later among the works it cites.