We describe a methodology for representing and optimizing user preferences on plans. Our approach differs from previous work on plan optimization in that we employ a generalizatio...
Gregg Rabideau, Barbara Engelhardt, Steve A. Chien
Most research in learning for planning has concentrated on efficiency gains. Another important goal is improving the quality of final plans. Learning to improve plan quality has b...
In this paper, we study strategies in incremental planning for ordering and grouping subproblems partitioned by the subgoals of a planning problem when each subproblem is solved b...
We describe a new approach to managing information quality (IQ) in an e-Science context, by allowing scientists to define the quality characteristics that are of importance in the...
Paolo Missier, Alun D. Preece, Suzanne M. Embury, ...
Current efficient planners employ an informed search guided by a heuristic function that is quite expensive to compute. Thus, ordering nodes in the search tree becomes a key issue,...