Temporal constraints pose a challenge for conditional planning, because it is necessary for a conditional planner to determine whether a candidate plan will satisfy the specified temporal constraints. This can be difficult, because temporal assignments that satisfy the constraints associated with one conditional branch may fail to satisfy the constraints along a different branch. In this paper we address this challenge by developing the Conditional Temporal Problem (CTP) formalism, an extension of standard temporal constraint-satisfaction processing models used in non-conditional temporal planning. Specifically, we augment temporal CSP fi'ameworks by (1) adding observation nodes, and (2) attaching labels to all nodes to indicate the situation(s) in which each will be executed. Our extended fi'amework allows for the construction of conditional plans that are guaranteed to satisfy complex temporal constraints. Importantly, this can be achieved even while allowing for decisions about the precise timing of actions to be postponed until execution time, thereby adding flexibility and making it possible to dynamically adapt the plan in response to the observations made during execution. We also show that, even for plans without explicit quantitative temporal constraints, our approach fLxes a problem in the earlier approaches to conditional planning, which resulted in their being incomplete
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