We extend hierarchical task network planning with task insertion (TIHTN) by introducing state constraints, called TIHTNS. We show that just as for TIHTN planning, all solutions of the TIHTNS planning problem can be obtained by acyclic decomposition and task insertion, entailing that its planexistence problem is decidable without any restriction on decomposition methods. We also prove that the e...

Many real-world planning problems are best modeled as infinite search space problems, using numeric fluents. Unfortunately, most planners and planning heuristics do not directly support such fluents. We propose a search space abstraction technique that compiles a planning problem with numeric fluents into a finite state propositional planning problem. To account for the loss of precision result...

Planning deals with the problem of finding a partially ordered sequence of actions (plan) that transfers the world from some initial state to a desired state. Causal relations between actions play a critical role here. Introduction of explicit time and resources into planning is an important step towards modeling real-life problems. In this paper we propose a suboptimal domainindependent planni...

Path planning quickly becomes computationally hard as the dimensionality of the state-space increases. In this paper, we present a planning algorithm intended to speed up path planning for high-dimensional state-spaces such as robotic arms. The idea behind this work is that while planning in a highdimensional state-space is often necessary to ensure the feasibility of the resulting path, large ...

This article is a first step in the direction of extending possibilistic planning to account for incomplete and imprecise knowledge of the world state. Fundamental definitions are given and the possibilistic planning problem is recast in this new setting. Finally, it is shown that, under certain conditions, possibilistic planning with imprecise and incomplete state descriptions is no harder tha...

Production planning and maintenance are two important problems in manufacturing systems. Despite the relationship exists between these two problems due to sudden failures and production capacity occupied by maintenance activities, each of these problems planned separately and as a result program and model efficiencies reduce in the real world. The aim of integrated production and maintena...

Planning has played an important role in many relevant areas of AI. The classical planning problem consists of the following task: Given a state of the world, several actions and their (deterministic) effects, find a sequence of actions (viz. a plan) to reach a certain goal state. In recent years, several successful logic-based approaches to classical planning have been proposed (cf. [33, 11, 6...

Indonesia's family planning program has been one of the most effective in the developing world in promoting contraceptive use and contributing to fertility transition. In evaluating why the program has worked, analysts have given much credit to a network of village family planning groups that developed from the 1970s to the 1990s and that blanketed the archipelago. These groups, composed primar...

Low-level motion planning techniques must be combined with high-level task planning formalisms to generate realistic plans that can be carried out by humans and robots. A representative example is planning for fenceless assembly cells where robots can collaborate seamlessly with humans to perform assembly tasks. Key constituent components include assembly sequence generation (Morato, Kaipa, and...

Many practical planning problems necessitate the generation of a plan under incomplete information about the state of the world. In this paper we propose the notion of AssumptionBased Planning. Unlike conformant planning, which attempts to find a plan under all possible completions of the initial state, an assumption-based plan supports the assertion of additional assumptions about the state of...