Planning for highly dynamic and uncertain real-world domains is difficult using current planning tools. These domains may be characterized by non-deterministic actions and the need to represent large real-valued state spaces. Classical planning considers only deterministic domains and sidesteps the issue of non-determinism. Real-valued variables are handled by requiring domains to either represent real variables as relative booleans (e.g. using on-table or on-block in the classical blocks world), or to explicitly enumerate each possible value for a real variable (e.g. using at11, at12, at 21, at22 for block position in a 2x2 blocks world). The former approach is a lossy transformation where positioning information is lost while the latter is subject to state explosion for large domains.
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