Switch to: References

Add citations

You must login to add citations.
  1. Discovering hidden structure in factored MDPs.Andrey Kolobov, Mausam & Daniel S. Weld - 2012 - Artificial Intelligence 189 (C):19-47.
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • Agent planning programs.Giuseppe De Giacomo, Alfonso Emilio Gerevini, Fabio Patrizi, Alessandro Saetti & Sebastian Sardina - 2016 - Artificial Intelligence 231 (C):64-106.
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  • Long-distance mutual exclusion for planning.Yixin Chen, Ruoyun Huang, Zhao Xing & Weixiong Zhang - 2009 - Artificial Intelligence 173 (2):365-391.
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • Least commitment in Graphplan.Michel Cayrol, Pierre Régnier & Vincent Vidal - 2001 - Artificial Intelligence 130 (1):85-118.
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • SAT-based planning in complex domains: Concurrency, constraints and nondeterminism.Claudio Castellini, Enrico Giunchiglia & Armando Tacchella - 2003 - Artificial Intelligence 147 (1-2):85-117.
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  • The factored policy-gradient planner.Olivier Buffet & Douglas Aberdeen - 2009 - Artificial Intelligence 173 (5-6):722-747.
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • Sequential Monte Carlo in reachability heuristics for probabilistic planning.Daniel Bryce, Subbarao Kambhampati & David E. Smith - 2008 - Artificial Intelligence 172 (6-7):685-715.
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • On the complexity of planning for agent teams and its implications for single agent planning.Ronen I. Brafman & Carmel Domshlak - 2013 - Artificial Intelligence 198 (C):52-71.
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • Reasoning with infinite stable models.Piero A. Bonatti - 2004 - Artificial Intelligence 156 (1):75-111.
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  • Planning as heuristic search.Blai Bonet & Héctor Geffner - 2001 - Artificial Intelligence 129 (1-2):5-33.
    Download  
     
    Export citation  
     
    Bookmark   39 citations  
  • Heuristics for planning with penalties and rewards formulated in logic and computed through circuits.Blai Bonet & Héctor Geffner - 2008 - Artificial Intelligence 172 (12-13):1579-1604.
    Download  
     
    Export citation  
     
    Bookmark  
  • Fast planning through planning graph analysis.Avrim L. Blum & Merrick L. Furst - 1997 - Artificial Intelligence 90 (1-2):281-300.
    Download  
     
    Export citation  
     
    Bookmark   54 citations  
  • Let's plan it deductively!W. Bibel - 1998 - Artificial Intelligence 103 (1-2):183-208.
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • Extracting mutual exclusion invariants from lifted temporal planning domains.Sara Bernardini, Fabio Fagnani & David E. Smith - 2018 - Artificial Intelligence 258 (C):1-65.
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • A heuristic search approach to planning with temporally extended preferences.Jorge A. Baier, Fahiem Bacchus & Sheila A. McIlraith - 2009 - Artificial Intelligence 173 (5-6):593-618.
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • Using temporal logics to express search control knowledge for planning.Fahiem Bacchus & Froduald Kabanza - 2000 - Artificial Intelligence 116 (1-2):123-191.
    Download  
     
    Export citation  
     
    Bookmark   24 citations  
  • Using genetic programming to learn and improve control knowledge.Ricardo Aler, Daniel Borrajo & Pedro Isasi - 2002 - Artificial Intelligence 141 (1-2):29-56.
    Download  
     
    Export citation  
     
    Bookmark  
  • Multi-agent path finding with mutex propagation.Han Zhang, Jiaoyang Li, Pavel Surynek, T. K. Satish Kumar & Sven Koenig - 2022 - Artificial Intelligence 311 (C):103766.
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • Constraint partitioning in penalty formulations for solving temporal planning problems.Benjamin W. Wah & Yixin Chen - 2006 - Artificial Intelligence 170 (3):187-231.
    Download  
     
    Export citation  
     
    Bookmark  
  • Branching and pruning: An optimal temporal POCL planner based on constraint programming.Vincent Vidal & Héctor Geffner - 2006 - Artificial Intelligence 170 (3):298-335.
    Download  
     
    Export citation  
     
    Bookmark   7 citations  
  • 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.
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  • Plan coordination by revision in collective agent based systems.Hans Tonino, André Bos, Mathijs de Weerdt & Cees Witteveen - 2002 - Artificial Intelligence 142 (2):121-145.
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  • State space search nogood learning: Online refinement of critical-path dead-end detectors in planning.Marcel Steinmetz & Jörg Hoffmann - 2017 - Artificial Intelligence 245 (C):1-37.
    Download  
     
    Export citation  
     
    Bookmark  
  • Planning the project management way: Efficient planning by effective integration of causal and resource reasoning in RealPlan.Biplav Srivastava, Subbarao Kambhampati & Minh B. Do - 2001 - Artificial Intelligence 131 (1-2):73-134.
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • Processes and continuous change in a SAT-based planner.Ji-Ae Shin & Ernest Davis - 2005 - Artificial Intelligence 166 (1-2):194-253.
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  • Representing and planning with interacting actions and privacy.Shashank Shekhar & Ronen I. Brafman - 2020 - Artificial Intelligence 278 (C):103200.
    Download  
     
    Export citation  
     
    Bookmark  
  • Learning from planner performance.Mark Roberts & Adele Howe - 2009 - Artificial Intelligence 173 (5-6):536-561.
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • Planning as satisfiability: parallel plans and algorithms for plan search.Jussi Rintanen, Keijo Heljanko & Ilkka Niemelä - 2006 - Artificial Intelligence 170 (12-13):1031-1080.
    Download  
     
    Export citation  
     
    Bookmark   9 citations  
  • Planning as satisfiability: Heuristics.Jussi Rintanen - 2012 - Artificial Intelligence 193 (C):45-86.
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • Multiobjective heuristic state-space planning.Ioannis Refanidis & Ioannis Vlahavas - 2003 - Artificial Intelligence 145 (1-2):1-32.
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • A Formal Characterisation of Hamblin’s Action-State Semantics.Chris Reed & Timothy J. Norman - 2007 - Journal of Philosophical Logic 36 (4):415 - 448.
    Hamblin's Action-State Semantics provides a sound philosophical foundation for understanding the character of the imperative. Taking this as our inspiration, in this paper we present a logic of action, which we call ST, that captures the clear ontological distinction between being responsible for the achievement of a state of affairs and being responsible for the performance of an action. We argue that a relativised modal logic of type RT founded upon a ternary relation over possible worlds integrated with a basic (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  • A Formal Characterisation of Hamblin’s Action-State Semantics.Chris Reed & Timothy J. Norman - 2007 - Journal of Philosophical Logic 36 (4):415-448.
    Hamblin’s Action-State Semantics provides a sound philosophical foundation for understanding the character of the imperative. Taking this as our inspiration, in this paper we present a logic of action, which we call ST, that captures the clear ontological distinction between being responsible for the achievement of a state of affairs and being responsible for the performance of an action. We argue that a relativised modal logic of type RT founded upon a ternary relation over possible worlds integrated with a basic (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  • The logical foundations of goal-regression planning in autonomous agents.John L. Pollock - 1998 - Artificial Intelligence 106 (2):267-334.
    Download  
     
    Export citation  
     
    Bookmark   8 citations  
  • Landmark-based approaches for goal recognition as planning.Ramon Fraga Pereira, Nir Oren & Felipe Meneguzzi - 2020 - Artificial Intelligence 279 (C):103217.
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  • Planning graph as the basis for deriving heuristics for plan synthesis by state space and CSP search.XuanLong Nguyen, Subbarao Kambhampati & Romeo S. Nigenda - 2002 - Artificial Intelligence 135 (1-2):73-123.
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • Generating diverse plans to handle unknown and partially known user preferences.Tuan Anh Nguyen, Minh Do, Alfonso Emilio Gerevini, Ivan Serina, Biplav Srivastava & Subbarao Kambhampati - 2012 - Artificial Intelligence 190 (C):1-31.
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • 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.
    Download  
     
    Export citation  
     
    Bookmark   12 citations  
  • Fuzzy rrDFCSP and planning.Ian Miguel & Qiang Shen - 2003 - Artificial Intelligence 148 (1-2):11-52.
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • Contingent planning under uncertainty via stochastic satisfiability.Stephen M. Majercik & Michael L. Littman - 2003 - Artificial Intelligence 147 (1-2):119-162.
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • 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.
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • Planning and acting in partially observable stochastic domains.Leslie Pack Kaelbling, Michael L. Littman & Anthony R. Cassandra - 1998 - Artificial Intelligence 101 (1-2):99-134.
    Download  
     
    Export citation  
     
    Bookmark   57 citations  
  • Towards efficient universal planning: A randomized approach.Peter Jonsson, Patrik Haslum & Christer Bäckström - 2000 - Artificial Intelligence 117 (1):1-29.
    Download  
     
    Export citation  
     
    Bookmark  
  • State-variable planning under structural restrictions: algorithms and complexity.Peter Jonsson & Christer Bäckström - 1998 - Artificial Intelligence 100 (1-2):125-176.
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • Gradient-based mixed planning with symbolic and numeric action parameters.Kebing Jin, Hankz Hankui Zhuo, Zhanhao Xiao, Hai Wan & Subbarao Kambhampati - 2022 - Artificial Intelligence 313 (C):103789.
    Download  
     
    Export citation  
     
    Bookmark  
  • Evaluating new options in the context of existing plans.John F. Horty & Martha E. Pollack - unknown - Artificial Intelligence 127 (2):199-220.
    This paper contributes to the foundations of a theory of rational choice for artificial agents in dynamic environments. Our work is developed within a theoretical framework, originally due to Bratman, that models resource-bounded agents as operating against the background of some current set of intentions, which helps to frame their subsequent reasoning. In contrast to the standard theory of rational choice, where options are evaluated in isolation, we therefore provide an analysis of situations in which the options presented to an (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • Conformant planning via heuristic forward search: A new approach.Jörg Hoffmann & Ronen I. Brafman - 2006 - Artificial Intelligence 170 (6-7):507-541.
    Download  
     
    Export citation  
     
    Bookmark   7 citations  
  • Complexity results for standard benchmark domains in planning.Malte Helmert - 2003 - Artificial Intelligence 143 (2):219-262.
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • CPCES: A planning framework to solve conformant planning problems through a counterexample guided refinement.Alban Grastien & Enrico Scala - 2020 - Artificial Intelligence 284 (C):103271.
    Download  
     
    Export citation  
     
    Bookmark  
  • Star-topology decoupled state space search.Daniel Gnad & Jörg Hoffmann - 2018 - Artificial Intelligence 257 (C):24-60.
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • Width-based search for multi agent privacy-preserving planning.Alfonso E. Gerevini, Nir Lipovetzky, Francesco Percassi, Alessandro Saetti & Ivan Serina - 2023 - Artificial Intelligence 318 (C):103883.
    Download  
     
    Export citation  
     
    Bookmark