Temporal plans permit significant flexibility in specifying the occurrence time of events. Plan execution can make good use of that flexibility. However, the advantage of executio...
Ioannis Tsamardinos, Nicola Muscettola, Paul H. Mo...
One difficulty with existing theoretical work on HTN planning is that it does not address some of the planning constructs that are commonly used in HTN planners for practical appl...
Spatio-temporal data sets arise when time-varying physical fields are discretized for simulation or analysis. Examples of time-varying fields are isothermal regions in the sea or ...
Reinforcement learning is an effective technique for learning action policies in discrete stochastic environments, but its efficiency can decay exponentially with the size of the ...
A novel method and a framework called Memory-Based Forecasting are proposed to forecast complex and timevarying natural patterns with the goal of supporting experts' decision...