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  1. Planning-based knowing how: A unified approach.Yanjun Li & Yanjing Wang - 2021 - Artificial Intelligence 296 (C):103487.
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  • Analyzing generalized planning under nondeterminism.Vaishak Belle - 2022 - Artificial Intelligence 307 (C):103696.
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  • Knowledge-based programs as succinct policies for partially observable domains.Bruno Zanuttini, Jérôme Lang, Abdallah Saffidine & François Schwarzentruber - 2020 - Artificial Intelligence 288 (C):103365.
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  • Epistemic planning: Perspectives on the special issue.Vaishak Belle, Thomas Bolander, Andreas Herzig & Bernhard Nebel - 2023 - Artificial Intelligence 316 (C):103842.
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  • A new representation and associated algorithms for generalized planning.Siddharth Srivastava, Neil Immerman & Shlomo Zilberstein - 2011 - Artificial Intelligence 175 (2):615-647.
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  • Conformant planning via symbolic model checking and heuristic search.A. Cimatti, M. Roveri & P. Bertoli - 2004 - Artificial Intelligence 159 (1-2):127-206.
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  • Decidability and complexity of action-based temporal planning over dense time.Nicola Gigante, Andrea Micheli, Angelo Montanari & Enrico Scala - 2022 - Artificial Intelligence 307 (C):103686.
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  • Strong planning under partial observability.Piergiorgio Bertoli, Alessandro Cimatti, Marco Roveri & Paolo Traverso - 2006 - Artificial Intelligence 170 (4-5):337-384.
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  • Automated composition of Web services via planning in asynchronous domains.Piergiorgio Bertoli, Marco Pistore & Paolo Traverso - 2010 - Artificial Intelligence 174 (3-4):316-361.
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  • Conformant plans and beyond: Principles and complexity.Blai Bonet - 2010 - Artificial Intelligence 174 (3-4):245-269.
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  • Automatic behavior composition synthesis.Giuseppe De Giacomo, Fabio Patrizi & Sebastian Sardiña - 2013 - Artificial Intelligence 196 (C):106-142.
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  • Task decomposition on abstract states, for planning under nondeterminism.Ugur Kuter, Dana Nau, Marco Pistore & Paolo Traverso - 2009 - Artificial Intelligence 173 (5-6):669-695.
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  • Knowing how to plan about planning: Higher-order and meta-level epistemic planning.Yanjun Li & Yanjing Wang - 2024 - Artificial Intelligence 337 (C):104233.
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  • State-set branching: Leveraging BDDs for heuristic search.Rune M. Jensen, Manuela M. Veloso & Randal E. Bryant - 2008 - Artificial Intelligence 172 (2-3):103-139.
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  • Understanding planning with incomplete information and sensing.Marcelo Oglietti - 2005 - Artificial Intelligence 164 (1-2):171-208.
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  • Plan aggregation for strong cyclic planning in nondeterministic domains.Ron Alford, Ugur Kuter, Dana Nau & Robert P. Goldman - 2014 - Artificial Intelligence 216 (C):206-232.
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  • Maintenance goals of agents in a dynamic environment: Formulation and policy construction.Chitta Baral, Thomas Eiter, Marcus Bjäreland & Mutsumi Nakamura - 2008 - Artificial Intelligence 172 (12-13):1429-1469.
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  • Algorithms and conditional lower bounds for planning problems.Krishnendu Chatterjee, Wolfgang Dvořák, Monika Henzinger & Alexander Svozil - 2021 - Artificial Intelligence 297 (C):103499.
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  • An Epistemic Approach to Nondeterminism: Believing in the Simplest Course of Events.James P. Delgrande & Hector J. Levesque - 2019 - Studia Logica 107 (5):859-886.
    This paper describes an approach for reasoning in a dynamic domain with nondeterministic actions in which an agent’s beliefs correspond to the simplest, or most plausible, course of events consistent with the agent’s observations and beliefs. The account is based on an epistemic extension of the situation calculus, a first-order theory of reasoning about action that accommodates sensing actions. In particular, the account is based on a qualitative theory of nondeterminism. Our position is that for commonsense reasoning, the world is (...)
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  • Domain-independent planning for services in uncertain and dynamic environments.Eirini Kaldeli, Alexander Lazovik & Marco Aiello - 2016 - Artificial Intelligence 236 (C):30-64.
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  • Sequential plan recognition: An iterative approach to disambiguating between hypotheses.Reuth Mirsky, Roni Stern, Kobi Gal & Meir Kalech - 2018 - Artificial Intelligence 260 (C):51-73.
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  • Deliberative acting, planning and learning with hierarchical operational models.Sunandita Patra, James Mason, Malik Ghallab, Dana Nau & Paolo Traverso - 2021 - Artificial Intelligence 299 (C):103523.
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  • Explain it as simple as possible, but no simpler – Explanation via model simplification for addressing inferential gap.Sarath Sreedharan, Siddharth Srivastava & Subbarao Kambhampati - 2025 - Artificial Intelligence 340 (C):104279.
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  • Applicability conditions for plans with loops: Computability results and algorithms.Siddharth Srivastava, Neil Immerman & Shlomo Zilberstein - 2012 - Artificial Intelligence 191-192 (C):1-19.
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