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  1. Reasoning agents in a dynamic world: The frame problem.Jozsef A. Toth - 1995 - Artificial Intelligence 73 (1-2):323-369.
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  • Remote Agent: to boldly go where no AI system has gone before.Nicola Muscettola, P. Pandurang Nayak, Barney Pell & Brian C. Williams - 1998 - Artificial Intelligence 103 (1-2):5-47.
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  • Computational research on interaction and agency.Philip E. Agre - 1995 - Artificial Intelligence 72 (1-2):1-52.
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  • Between epistemology and hermeneutics.Dimitri Ginev - 1995 - Science & Education 4 (2):147-159.
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  • Explicatures are NOT Cancellable.Alessandro Capone - 2013 - In Perspectives on Linguistic Pragmatics. Cham: Springer. pp. 131-151.
    Explicatures are not cancellable. Theoretical considerations.
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  • Kernel functions for case-based planning.Ivan Serina - 2010 - Artificial Intelligence 174 (16-17):1369-1406.
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  • The computational complexity of propositional STRIPS planning.Tom Bylander - 1994 - Artificial Intelligence 69 (1-2):165-204.
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  • Localized planning with action-based constraints.Amy L. Lansky - 1998 - Artificial Intelligence 98 (1-2):49-136.
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  • A general programming language for unified planning and control.Richard Levinson - 1995 - Artificial Intelligence 76 (1-2):319-375.
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  • Expressive equivalence of planning formalisms.Christer Bäckström - 1995 - Artificial Intelligence 76 (1-2):17-34.
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  • Complexity, decidability and undecidability results for domain-independent planning.Kutluhan Erol, Dana S. Nau & V. S. Subrahmanian - 1995 - Artificial Intelligence 76 (1-2):75-88.
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  • Planning as refinement search: a unified framework for evaluating design tradeoffs in partial-order planning.Subbarao Kambhampati, Craig A. Knoblock & Qiang Yang - 1995 - Artificial Intelligence 76 (1-2):167-238.
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  • Acquiring search-control knowledge via static analysis.Oren Etzioni - 1993 - Artificial Intelligence 62 (2):255-301.
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  • (1 other version)The logical foundations of goal-regression planning in autonomous agents.John L. Pollock - 1998 - Artificial Intelligence 106 (2):267-334.
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  • Embodiment versus memetics.Joanna J. Bryson - 2007 - Mind and Society 7 (1):77-94.
    The term embodiment identifies a theory that meaning and semantics cannot be captured by abstract, logical systems, but are dependent on an agent’s experience derived from being situated in an environment. This theory has recently received a great deal of support in the cognitive science literature and is having significant impact in artificial intelligence. Memetics refers to the theory that knowledge and ideas can evolve more or less independently of their human-agent substrates. While humans provide the medium for this evolution, (...)
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  • Explaining and repairing plans that fail.Kristian J. Hammond - 1990 - Artificial Intelligence 45 (1-2):173-228.
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  • Interpreting a dynamic and uncertain world: task-based control.Richard J. Howarth - 1998 - Artificial Intelligence 100 (1-2):5-85.
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  • Stochastic dynamic programming with factored representations.Craig Boutilier, Richard Dearden & Moisés Goldszmidt - 2000 - Artificial Intelligence 121 (1-2):49-107.
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  • Artificial Intelligence and Law: How to Get There from Here.L. Thorne Mccarty - 1990 - Ratio Juris 3 (2):189-200.
    . This paper offers a survey of the current state of Artificial Intelligence and Law, and makes recommendations for future research. Two main areas of investigation are discussed: the practical work on intelligent legal information systems, and the theoretical work on computational models of legal reasoning. In both areas, the knowledge representation problem is identified as the most important issue facing this field.
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  • Processes and continuous change in a SAT-based planner.Ji-Ae Shin & Ernest Davis - 2005 - Artificial Intelligence 166 (1-2):194-253.
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  • Reasoning about partially ordered events.Thomas Dean & Mark Boddy - 1988 - Artificial Intelligence 36 (3):375-399.
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  • Embedding decision-analytic control in a learning architecture.Oren Etzioni - 1991 - Artificial Intelligence 49 (1-3):129-159.
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  • Theory and algorithms for plan merging.David E. Foulser, Ming Li & Qiang Yang - 1992 - Artificial Intelligence 57 (2-3):143-181.
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  • A theory of conflict resolution in planning.Qiang Yang - 1992 - Artificial Intelligence 58 (1-3):361-392.
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  • Time and modality in a natural language interface to a planning system.R. S. Crouch & S. G. Pulman - 1993 - Artificial Intelligence 63 (1-2):265-304.
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  • Plan-based integration of natural language and graphics generation.Wolfgang Wahlster, Elisabeth André, Wolfgang Finkler, Hans-Jürgen Profitlich & Thomas Rist - 1993 - Artificial Intelligence 63 (1-2):387-427.
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  • Fast planning through planning graph analysis.Avrim L. Blum & Merrick L. Furst - 1997 - Artificial Intelligence 90 (1-2):281-300.
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  • Knowledge and communication: A first-order theory.Ernest Davis - 2005 - Artificial Intelligence 166 (1-2):81-139.
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  • Vision, instruction, and action.Damian M. Lyons - 1995 - Artificial Intelligence 73 (1-2):387-401.
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  • A preliminary analysis of the Soar architecture as a basis for general intelligence.Paul S. Rosenbloom, John E. Laird, Allen Newell & Robert McCarl - 1991 - Artificial Intelligence 47 (1-3):289-325.
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  • Representations of commonsense knowledge.Daniel S. Weld - 1993 - Artificial Intelligence 61 (1):113-120.
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  • Automatically selecting and using primary effects in planning: theory and experiments.Eugene Fink & Qiang Yang - 1997 - Artificial Intelligence 89 (1-2):285-315.
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  • An algorithm for probabilistic planning.Nicholas Kushmerick, Steve Hanks & Daniel S. Weld - 1995 - Artificial Intelligence 76 (1-2):239-286.
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  • A logic of time, chance, and action for representing plans.Peter Haddawy - 1996 - Artificial Intelligence 80 (2):243-308.
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  • Permissive planning: extending classical planning to uncertain task domains.Gerald F. DeJong & Scott W. Bennett - 1997 - Artificial Intelligence 89 (1-2):173-217.
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  • A geometric approach to error detection and recovery for robot motion planning with uncertainty.Bruce R. Donald - 1988 - Artificial Intelligence 37 (1-3):223-271.
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  • On the evaluation of agent behaviors.Amol Dattatraya Mali - 2003 - Artificial Intelligence 143 (1):1-17.
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  • Calculating criticalities.A. Bundy, F. Giunchiglia, R. Sebastiani & T. Walsh - 1996 - Artificial Intelligence 88 (1-2):39-67.
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  • Coordinating Agents in Design: A Formal Analysis.U. V. Johar - 1998 - Journal of Intelligent Systems 8 (3-4):291-314.
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  • On the nature and role of modal truth criteria in planning.Subbarao Kambhampati & Dana S. Nau - 1996 - Artificial Intelligence 82 (1-2):129-155.
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  • The scope and limits of simulation in automated reasoning.Ernest Davis & Gary Marcus - 2016 - Artificial Intelligence 233 (C):60-72.
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  • A validation-structure-based theory of plan modification and reuse.Subbarao Kambhampati & James A. Hendler - 1992 - Artificial Intelligence 55 (2-3):193-258.
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  • Planning parallel actions.A. R. Lingard & E. B. Richards - 1998 - Artificial Intelligence 99 (2):261-324.
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  • World modeling for the dynamic construction of real-time control plans.David J. Musliner, Edmund H. Durfee & Kang G. Shin - 1995 - Artificial Intelligence 74 (1):83-127.
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  • On the computational complexity of temporal projection, planning, and plan validation.Bernhard Nebel & Christer Bäckström - 1994 - Artificial Intelligence 66 (1):125-160.
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  • Incremental Knowledge-acquisition for Complex Multi-agent Environments.Angela Finlayson - forthcoming - Philosophy.
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  • Multi-contributor causal structures for planning: a formalization and evaluation.Subbarao Kambhampati - 1994 - Artificial Intelligence 69 (1-2):235-278.
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  • Algorithms for propagating resource constraints in AI planning and scheduling: Existing approaches and new results.Philippe Laborie - 2003 - Artificial Intelligence 143 (2):151-188.
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  • Incrementality and Intention-Recognition in Utterance Processing.Eleni Gregoromichelaki, Ruth Kempson, Matthew Purver, Gregory Mills, Ronnie Cann, Wilfried Meyer-Viol & Patrick G. T. Healey - 2011 - Dialogue and Discourse 2 (1):199-232.
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  • On point-based temporal disjointness.Alfonso Gerevini & Lenhart Schubert - 1994 - Artificial Intelligence 70 (1-2):347-361.
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