Several motion planning methods using networks of randomly generated nodes in the free space have been shown to perform well in a number of cases, however their performance degrad...
Steven A. Wilmarth, Nancy M. Amato, Peter F. Still...
Many problems used in AI planning including Blocks, Logistics, Gripper, Satellite, and others lack the interactions that characterize puzzles and can be solved nonoptimally in low...
Currently, among the fastest approaches to AI task planning we find many forward-chaining heuristic planners, as FF. Most of their good performance comes from the use of domain-i...
A staggering number of multimedia applications are being introduced every day. Yet, the inordinate delays encountered in retrieving multimedia documents make it difficult to use t...
This paper presents snlp+ebl, the first implementation of explanation based learning techniques for a partial order planner. We describe the basic learning framework of snlp+ebl, ...