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Planning as constraint satisfaction: Solving the planning graph by compiling it into CSP
Artificial Intelligence 132 (2):151-182 (2001)
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Citations of this work
Concise finite-domain representations for PDDL planning tasks.Malte Helmert - 2009 - Artificial Intelligence 173 (5-6):503-535.
Planning as satisfiability: parallel plans and algorithms for plan search.Jussi Rintanen, Keijo Heljanko & Ilkka Niemelä - 2006 - Artificial Intelligence 170 (12-13):1031-1080.
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.
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.
Extracting mutual exclusion invariants from lifted temporal planning domains.Sara Bernardini, Fabio Fagnani & David E. Smith - 2018 - Artificial Intelligence 258 (C):1-65.
References found in this work
Fast planning through planning graph analysis.Avrim L. Blum & Merrick L. Furst - 1997 - Artificial Intelligence 90 (1-2):281-300.
Temporal constraint networks.Rina Dechter, Itay Meiri & Judea Pearl - 1991 - Artificial Intelligence 49 (1-3):61-95.
On the relations between intelligent backtracking and failure-driven explanation-based learning in constraint satisfaction and planning.Subbarao Kambhampati - 1998 - Artificial Intelligence 105 (1-2):161-208.
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.
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