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Fast Downward Stone Soup is a sequential portfolio planner that uses various heuristics and search algorithms that have been implemented in the Fast Downward planning system. We present a simple general method for concocting " planner soups " , sequential portfolios of planning algorithms, and describe the actual recipes used for Fast Downward Stone Soup in(More)
In this work, we present the FD-Autotune learning planning system, which is based on the idea of domain-specific configuration of the latest, highly parametric version of the Fast Downward Planning Framework by means of a generic automated algorithm configuration procedure. We describe how the extremely large configuration space of Fast Downward was(More)
Domain-independent planning is one of the foundational areas in the field of Artificial Intelligence. A description of a planning task consists of an initial world state, a goal, and a set of actions for modifying the world state. The objective is to find a sequence of actions, that is, a plan, that transforms the initial world state into a goal state. In(More)
Goal recognition design involves the offline analysis of goal recognition models by formulating measures that assess the ability to perform goal recognition within a model and finding efficient ways to compute and optimize them. In this work we present goal recognition design for non-optimal agents, which extends previous work by accounting for agents that(More)
Fast Downward Stone Soup is a sequential portfolio planner that uses various heuristics and search algorithms that have been implemented in the Fast Downward planning system. We present a simple general method for concocting " planner soups " , sequential portfolios of planning algorithms, and describe the actual recipes used for Fast Downward Stone Soup in(More)