Eliseo Marzal

SimPlanner: An Execution-Monitoring System for Replanning in Dynamic Worlds

In this paper we present SimPlanner, an integrated planning and execution-monitoring system. SimPlanner allows the user to monitor the execution of a plan, interrupt this monitoring process to introduce new information from the world and repair the plan to get it adapted to the new situation.

STeLLa: An Optimal Sequential and Parallel Planner

In the last few years, the field of planning in AI has experimented a great advance. Nowadays, one can use planners that solve complex problems in a few seconds. However, building good quality plans has not been a main issue. In this paper, we introduce a planning system whose aim is obtaining the optimal solution w.r.t. the number of actions and maintaining as maximum number of parallel actions as possible.

Full Extraction of Landmarks in Propositional Planning Tasks

One can find in the literature several approaches aimed at finding landmarks and orderings, each claiming to obtain an improvement over the first original approach. In this paper we propose a complementary view to landmarks exploitation that combines the advantages of each approach and come up with a novel technique that outperforms each individual method.

STeLLa v2.0: Planning with Intermediate Goals

In the last few years, AI planning techniques have experimented a great advance. One of the reasons for this big expansion is the International Planning Competition (IPC), which enforces the definition of language standards as PDDL+ and new benchmarks. In this paper, we present the new features of STeLLa, a planner that participated in the last IPC, held in Toulouse last April. STeLLa is a forward search planner that builds intermediate goals to ease the resolution of the planning problem.

Temporal Landmarks for Overconstrained Planning Problems with Deadlines

In this paper we present a temporal planning approach for handling problems with deadlines. The model relies on the extraction of temporal landmarks from the problem and the construction of a landmarks graph as a skeleton of the solution plan. Partial plans in the search tree that are not compliant with the information comprised in this graph are pruned. We introduce a novel search scheme that builds a landmarks graph in each tree node and which notably improves the rate of detection of unsolvable problems.

Temporal landmark graphs for solving overconstrained planning problems

This paper presents TempLM, a novel approach for handling temporal planning problems with deadlines. The proposal revolves around the concept of temporal landmark, a proposition that must be necessarily true in all solution plans to achieve the problem goals within their deadlines. The temporal landmarks extracted from the problem form a landmarks graph where nodes are landmarks and edges represent temporal as well as causal relationships between landmarks. The graph comprises information about which propositions and when these propositions must be achieved in a solution plan, information that is later used to guide the search process as well as reduce the search space. Thus, the partial plans of the search tree that are not compliant with the information comprised in this graph are pruned. We present an exhaustive experimentation evaluation in overconstrained and unsolvable problems and we compare the performance of TempLM with other state-of-the-art planners. The results will show the efficiency of TempLM in the detection of unsolvable problems.

Scheduling a plan with delays in time: a CSP approach

In many realistic planning domains, the exact duration of actions is only known at the instant of executing the action. This is the case, for instance, of temporal domains where it is common to find external factors that cause a delay in the execution of actions. In this paper we present an approach to obtain a plan for a temporal domain with delays. Our approach consists in combining a planning process, from which a temporal plan is obtained, and a scheduling process to allocate (instantiate) such a temporal plan over a time line.

SPLIN: Una heramienta para el diseño,ejecución y evaluación de problemas de planificación

Resumen. Este trabajo presenta el diseño e implementación de un Sistema de PLanificación INteligente (SPLIN) que se compone de dos módulos principales: un compilador para el lenguaje de planificación y un Planificador de Orden Parcial (POP). SPLIN está integramente desarrollado en C, dispone de un lenguaje de planificación de fácil utilización e incorpora la técnica de menor compromiso (least commitment) [Weld94] tanto en la ordenación de pasos durante el desarrollo del plan como en el tratamiento de variables. Este último aspecto permite obtener resultados altamente satisfactorios frente a otros planificadores de orden parcial. La versión de SPLIN que se presenta en este artículo es un primer prototipo que se ha realizado en el grupo GTI-IA de la Universidad Politécnica de Valencia.