Many planning domains have to deal with temporal features that can be expressed using durations that are associated to actions. Unfortunately, the conservative model of actions used in many existing temporal planners is not adequate for domains which require more expressive models. This paper presents a temporal planning approach that combines the principles of Graphplan and TGP and uses the in...

Most of the research in Automated Planning relies on the evaluation of different techniques over a set of benchmarks. The generation of planning tasks for these benchmarks is done using generators coded ad-hoc. Instead, we propose an approach for generating planning problems automatically given the domain definition and some declarative semanticsrelated information provided by the user. The app...

This article presents a view of planning as o task supported by o dynamic memory. This view attempts to ingegrote models of memory, learning, and planning into a single system that learns about planning by creating new plans and analyzing how they interact with the world. We call this view of planning case-based planning. A case-based planner makes use of its own past experience in developing n...

The contribution of the paper is a high performance pathplanning algorithm designed to be used within a multi-agent planning framework solving a UAV collision avoidance problem. Due to the lack of benchmark examples and available algorithms for 3D+time planning, the algorithm performance has been compared in the classical domain of path planning in grids with blocked and unblocked cells. The Ac...