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  1. Proof Systems for Planning Under Cautious Semantics.Yuping Shen & Xishun Zhao - 2013 - Minds and Machines 23 (1):5-45.
    Planning with incomplete knowledge becomes a very active research area since late 1990s. Many logical formalisms introduce sensing actions and conditional plans to address the problem. The action language $\mathcal{A}_{K}$ invented by Son and Baral is a well-known framework for this purpose. In this paper, we propose so-called cautious and weakly cautious semantics for $\mathcal{A}_{K}$ , in order to allow an agent to generate and execute reliable plans in safety-critical environments. Intuitively speaking, cautious and weakly cautious semantics enable the agent (...)
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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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  • 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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  • Knowledge, action, and the frame problem.Richard B. Scherl & Hector J. Levesque - 2003 - Artificial Intelligence 144 (1-2):1-39.
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  • Common-sense reasoning as proto-scientific agent activity.Pierangelo Dell'Acqua & Luís Moniz Pereira - 2004 - Journal of Applied Logic 2 (4):385-407.
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  • Reasoning about Sensing Actions in Domains with Multi-Valued Fluents.Tran Cao Son, Phan Huy Tu & Xin Zhang - 2005 - Studia Logica 79 (1):135-160.
    In this paper, we discuss the weakness of current action languages for sensing actions with respect to modeling domains with multi-valued fluents. To address this problem, we propose a language with sensing actions and multi-valued fluents, called AMK, provide a transition function based semantics for the language, and demonstrate its use through several examples from the literature. We then define the entailment relationship between action theories and queries in AMK, denoted by ⊧AMK, and discuss some properties about AMK.
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  • A lightweight epistemic logic and its application to planning.Martin C. Cooper, Andreas Herzig, Faustine Maffre, Frédéric Maris, Elise Perrotin & Pierre Régnier - 2021 - Artificial Intelligence 298 (C):103437.
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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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  • Computational complexity of planning and approximate planning in the presence of incompleteness.Chitta Baral, Vladik Kreinovich & Raúl Trejo - 2000 - Artificial Intelligence 122 (1-2):241-267.
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  • Undoing the effects of action sequences.Thomas Eiter, Esra Erdem & Wolfgang Faber - 2008 - Journal of Applied Logic 6 (3):380-415.
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  • A generic approach to planning in the presence of incomplete information: Theory and implementation.Son Thanh To, Tran Cao Son & Enrico Pontelli - 2015 - Artificial Intelligence 227 (C):1-51.
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  • Approximation of action theories and its application to conformant planning.Phan Huy Tu, Tran Cao Son, Michael Gelfond & A. Ricardo Morales - 2011 - Artificial Intelligence 175 (1):79-119.
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  • Database semantics for natural language.Roland Hausser - 2001 - Artificial Intelligence 130 (1):27-74.
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  • An action language for multi-agent domains.Chitta Baral, Gregory Gelfond, Enrico Pontelli & Tran Cao Son - 2022 - Artificial Intelligence 302 (C):103601.
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  • Knowledge updates: Semantics and complexity issues.Chitta Baral & Yan Zhang - 2005 - Artificial Intelligence 164 (1-2):209-243.
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  • Logic and AI in China: An Introduction. [REVIEW]Fenrong Liu & Kaile Su - 2013 - Minds and Machines 23 (1):1-4.
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  • Practical reasoning about knowledge states for open world planning with sensing.Tamara Babaian & James G. Schmolze - 2009 - Journal of Applied Non-Classical Logics 19 (1):7-41.
    We present a representation for reasoning and planning with an incomplete state description (open-world) called PSIPLAN-S. The presented formalism has several properties critical for application domains with a large degree of incompleteness in the state description, particularly, in domains with a large or unknown set of all objects. The formalism offers (1) considerably expressive state and goal description language, that includes limited universal quantification, (2) representation of sensing actions and knowledge goals, (3) a correct and complete state update procedure, and (...)
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