New Heuristics for Planning with Action Costs
Classical planning is the problem of nding a sequence of actions that take an agent from an initial state to a desired goal situation, assuming deter- ministic outcomes for actions and perfect information. Satis cing planning seeks to quickly nd low-cost solutions with no guarantees of optimality. T...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2010 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/7570 |
| Acceso en línea: | http://www.tdx.cat/TDX-0210111-150546 http://hdl.handle.net/10803/7570 |
| Access Level: | acceso abierto |
| Palabra clave: | unfolded hyperpath STRIPS Steiner tree soft goal compilation set-additive heuristic soft goal search satisficing planning relaxed plan heuristic relaxed plan relaxation recursive conditioning planning domain planning landmark optimal planning oversubscription independence independence assumption inference landmark heuristic hypergraph heuristic heuristic search graph dtree delete relaxation cost constraint satisfaction conjunctive landmark classical planning complexity choice variable Bayesian network additive heuristic algorithm AND/OR graph action cost 62 |
| Sumario: | Classical planning is the problem of nding a sequence of actions that take an agent from an initial state to a desired goal situation, assuming deter- ministic outcomes for actions and perfect information. Satis cing planning seeks to quickly nd low-cost solutions with no guarantees of optimality. The most e ective approach for satis cing planning has proved to be heuristic search using non-admissible heuristics. In this thesis, we introduce several such heuristics that are able to take into account costs on actions, and there- fore try to minimize the more general metric of cost, rather than length, of plans, and investigate their properties and performance. In addition, we show how the problem of planning with soft goals can be compiled into a classical planning problem with costs, a setting in which cost-sensitive heuristics such as those presented here are essential. |
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