Automated planning addresses the problem of generating a sequence of actions to satisfy given goal conditions for a constructed model of the world. In recent planning approaches heuristic guidance is used to lead the search towards the goal. The focus of this work is on domains where plan quality is assessed with plan metrics. A discussion of the impact of a popular relaxed planning graph heuri...

Multi-agent systems often exhibit rich parallelism among agents. It is desirable in a multi-agent planner to explicitly represent parallel actions. This paper presents an approach for generating parallel execution plans based on the planning graph analysis. Instead of representing a planning problem by STRIPS operators, we model multi-agent planning domains using Predicate/Transition (PrT) nets...

We introduce a simple variation of the additive heuristic used in the HSP planner that combines the benefits of the original additive heuristic, namely its mathematical formulation and its ability to handle non-uniform action costs, with the benefits of the relaxed planning graph heuristic used in FF, namely its compatibility with the highly effective enforced hill climbing search along with it...

We present an algorithm for combining natural language processing (NLP) and realtime robot motion planning to automatically generate safe robot movements. We present a novel method to map the complex natural language commands into appropriate cost function and constraint parameters for optimizationbased motion planning. Given NLP commands, we generate a factor graph named Dynamic Grounding Grap...

In this paper we study the complexity of STRIPS planning when operators have a single effect. In particular, we show how the structure of the domain’s causal graph influences the complexity of planning. Causal graphs relate between preconditions and effects of domain operators. They were introduced by Williams and Nayak, who studied unary operator domains because of their direct applicability t...

The tradeoffformulation task is to identify the central issues in a decision problem by recognizing strategies that are inadmissible on qualitative grounds. SUDO-PLANNER formulates tradeoffs for an example medical decision problem by proving decisiontheoretically that certain plan classes are dominated based on a knowledge base of qualitative relations in the domain. The classical planning repr...

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 fluents, the quality of the solutions can ...