Alfonso Gerevini

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The notion of plan quality in automated planning is a practically very important issue. In many real-world planning domains, we have to address problems with a large set of solutions, or with a set of goals that cannot all be achieved. In these problems, it is important to generate plans of good or optimal quality achieving all problem goals (if possible)(More)
We present LPG, a fast planner using local search for solving planning graphs. LPG can use various heuristics based on a parametrized objective function. These parameters weight different types of inconsistencies in the partial plan represented by the current search state, and are dynamically evaluated during search using Lagrange multipliers. LPG’s basic(More)
We present some techniques for planning in domains specified with the recent standard language pddl2.1, supporting “durative actions” and numerical quantities. These techniques are implemented in lpg, a domain-independent planner that took part in the 3rd International Planning Competition (IPC). lpg is an incremental, any time system producing(More)
The international planning competition (IPC) is an important driver for planning research. The general goals of the IPC include pushing the state of the art in planning technology by posing new scientific challenges, encouraging direct comparison of planning systems and techniques, developing and improving a common planning domain definition language, and(More)
The ultimate objective in planning is to construct plans for execution. However, when a plan is executed in a real environment it can encounter differences between the expected and actual context of execution. These differences can manifest as divergences between the expected and observed states of the world, or as a change in the goals to be achieved by(More)
In many read-world planning domains, generating good plan quality is a central issue. This is especially true for problems with many solutions, or with many goals that cannot be achieved altogether. We propose an extension to the PDDL language that aims at a better characterization of plan quality by allowing the user to express strong and soft state(More)
The treatment of exogenous events in planning is practically important in many realworld domains where the preconditions of certain plan actions are affected by such events. In this paper we focus on planning in temporal domains with exogenous events that happen at known times, imposing the constraint that certain actions in the plan must be executed during(More)
Dealing with numerical information is practically important in many real-world planning domains where the executability of an action can depend on certain numerical conditions, and the action effects can consume or renew some critical continuous resources, which in PDDL can be represented by numerical fluents. When a planning problem involves numerical(More)
Fast plan adaptation is important in many AIapplications. From a theoretical point of view, in the worst case adapting an existing plan to solve a new problem is no more efficient than a complete regeneration of the plan. However, in practice plan adaptation can be much more efficient than plan generation, especially when the adapted plan can be obtained by(More)
Information about the size of spatial regions is often easily accessible and, when combined with other types of spatial information, it can be practically very useful. In this paper we introduce four classes of qualitative and metric size constraints, and we study their integration with the Region Connection Calculus RCC-8, a well-known approach to(More)