— We present an algorithm that probabilistically covers a bounded region of the state space of a nonlinear system with a sparse tree of feedback stabilized trajectories leading t...
Abstract— We propose a planning algorithm that allows usersupplied domain knowledge to be exploited in the synthesis of information feedback policies for systems modeled as parti...
Salvatore Candido, James C. Davidson, Seth Hutchin...
The heuristics used for planning and search often take the pattern databases generated from abstracted versions of the given state space. Pattern databases are typically stored p ...
Temporally extended goals (TEGs) refer to properties that must hold over intermediate and/or final states of a plan. Current planners for TEGs prune the search space during planni...
Planners from the family of Graphplan (Graphplan, IPP, STAN...) are presently considered as the most efficient ones on numerous planning domains. Their partially ordered plans can...