We present a general framework for studying heuristics for planning in the belief space. Earlier work has focused on giving implementations of heuristics that work well on benchma...
We address distributed real-time applications represented by systems of non-preemptive dependent periodic tasks. This system is described by an acyclic directed graph. Because the...
Many current state-of-the-art planners rely on forward heuristic search. The success of such search typically depends on heuristic distance-to-the-goal estimates derived from the ...
Consensus clustering is the problem of reconciling clustering information about the same data set coming from different sources or from different runs of the same algorithm. Cast ...
g Without a Heuristic: Efficient Use of Abstraction Bradford Larsen, Ethan Burns, Wheeler Ruml Department of Computer Science University of New Hampshire Durham, NH 03824 USA blars...
Bradford John Larsen, Ethan Burns, Wheeler Ruml, R...
We introduce a simple variation of the additive heuristic used in the HSP planner that combines the benefits of the original additive heuristic, namely its mathematical formulation...
“Heuristic synergy” refers to improvements in search performance when the decisions made by two or more heuristics are combined. This paper considers combinations based on prod...
Though attention to evaluating human-robot interfaces has increased in recent years, there are relatively few reports of using evaluation tools during the development of humanrobo...
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...
Planning problems are often formulated as heuristic search. The choice of the heuristic function plays a significant role in the performance of planning systems, but a good heuris...