Name
Abstract | ||
|---|---|---|
This paper studies the solving of finite-domain action planning problems with discrete action costs and soft constraints. For sequential optimal planning, a symbolic perimeter database heuristic is addressed in a bucket implementation of A*. For computing net-benefits, we propose symbolic branch-and-bound search together with some search refinements. The net-benefit we optimize is the total benefit of satisfying the goals, minus the total action cost to achieve them. This results in an objective function to be minimized that is a linear expression over the violation of the preferences added to the action cost total. |
Year | Venue | Keywords |
|---|---|---|
2009 | IJCAI | symbolic branch-and-bound search,finite-domain action planning problem,bucket implementation,total benefit,action cost total,sequential optimal planning,search refinement,total action cost,optimal symbolic planning,symbolic perimeter database heuristic,discrete action cost,branch and bound,satisfiability,objective function |
Field | DocType | Citations |
Heuristic,Mathematical optimization,Computer science,Optimal planning,Action planning | Conference | 18 |
PageRank | References | Authors |
0.65 | 21 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefan Edelkamp | 1 | 1557 | 125.46 |
| Peter Kissmann | 2 | 181 | 13.93 |