AAAI Publications, Twenty-Fourth AAAI Conference on Artificial Intelligence

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Planning in Dynamic Environments: Extending HTNs with Nonlinear Continuous Effects
Matthew Molineaux, Matthew Klenk, David Aha

Last modified: 2010-07-04


Planning in dynamic continuous environments requires reasoning about nonlinear continuous effects, which previous Hierarchical Task Network (HTN) planners do not support. In this paper, we extend an existing HTN planner with a new state projection algorithm. To our knowledge, this is the first HTN planner that can reason about nonlinear continuous effects. We use a wait action to instruct this planner to consider continuous effects in a given state. We also introduce a new planning domain to demonstrate the benefits of planning with nonlinear continuous effects. We compare our approach with a linear continuous effects planner and a discrete effects HTN planner on a benchmark domain, which reveals that its additional costs are largely mitigated by domain knowledge. Finally, we present an initial application of this algorithm in a practical domain, a Navy training simulation, illustrating the utility of this approach for planning in dynamic continuous environments.


HTN Planning; Continuous Planning; Mixed Discrete-Continuous Planning

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