TY - GEN
T1 - Understanding and extending Graphplan
AU - Kambhampati, Subbarao
AU - Parker, Eric
AU - Lambrecht, Eric
PY - 1997
Y1 - 1997
N2 - We provide a reconstruction of Blum and Furst's Graphplan algorithm, and use the reconstruction to extend and improve the original algorithm in several ways. In our reconstruction, the process of growing the planning-graph and inferring mutex relations corresponds to doing forward state-space refinement over disjunctively represented plans. The backward search phase of Graphplan corresponds to solving a binary dynamic constraint satisfaction problem. Our reconstruction sheds light on the sources of strength of Graph-plan. We also use the reconstruction to explain how Graphplan can be made goal-directed, how it can be extended to handle actions with conditional effects, and how backward state-space refinement can be generalized to apply to disjunctive plans. Finally, we discuss how the backward search phase of Graphplan can be improved by applying techniques from CSP literature, and by teasing apart planning and scheduling (resource allocation) phases in Graphplan.
AB - We provide a reconstruction of Blum and Furst's Graphplan algorithm, and use the reconstruction to extend and improve the original algorithm in several ways. In our reconstruction, the process of growing the planning-graph and inferring mutex relations corresponds to doing forward state-space refinement over disjunctively represented plans. The backward search phase of Graphplan corresponds to solving a binary dynamic constraint satisfaction problem. Our reconstruction sheds light on the sources of strength of Graph-plan. We also use the reconstruction to explain how Graphplan can be made goal-directed, how it can be extended to handle actions with conditional effects, and how backward state-space refinement can be generalized to apply to disjunctive plans. Finally, we discuss how the backward search phase of Graphplan can be improved by applying techniques from CSP literature, and by teasing apart planning and scheduling (resource allocation) phases in Graphplan.
UR - http://www.scopus.com/inward/record.url?scp=21944446103&partnerID=8YFLogxK
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U2 - 10.1007/3-540-63912-8_91
DO - 10.1007/3-540-63912-8_91
M3 - Conference contribution
AN - SCOPUS:21944446103
SN - 3540639128
SN - 9783540639121
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 260
EP - 272
BT - Recent Advances in AI Planning - 4th European Conference on Planning, ECP 1997, Proceedings
PB - Springer Verlag
T2 - 4th European Conference on Planning, ECP 1997
Y2 - 24 September 1997 through 26 September 1997
ER -