in the same order that those steps will be executed. We also examine how introducing the total-order restriction into HTN planning affects its expressive power, and propose a way to relax the total-order restriction to increase its expressive power and range of applicability.

Despite the extensive development of first-principles plan-ning in recent years, planning applications are still primar-ily developed using knowledge-based planners which can ex-ploit domain-specific heuristics and weaker domain models. Hierarchical Task Network (HTN) planners capture domain

can be represented using an ex-tensible composition template or pattern. In prior work, a flow pattern language called Cascade and its corresponding spe-cialized planner have shown the best performance in these do-mains. In this paper, we propose the use of Hierarchical Task Network (HTN) planning

Abstract. Constraint satisfaction problems provide strong formalism for modeling variety of real life problems. This paper presents a work currently in progress of which the goal is an application of the CSP formalism on hierarchical task network planning domain. An encoding of HTN planning

experiments demonstrate the application of a general purpose deliberative planner in the domain of mobile service robots. One challenging problem arises from the fact that adaptive AI-based planners presume the closed-world assumption (CWA) and are therefore unable to deal with incomplete information. Unknown

In this paper we explore a principled, integrated approach to the process of creating complex planning applications and introduce and evaluate a new hybrid task-reduction planner called HyHTN. In the short term our work is leading to an experimental research platform for investigating the synergy

Our research concerns formal, expressive, objectcentred languages and tools for use in engineering domains for planning applications. In this paper we extend our recent work on an object-centred language for encoding precondition planning domains to a language called OCL h , designed for HTN

Agreat challenge in developing planning systems for practical applications is the difficulty of acquiring the domain information needed to guide such systems. This paper describes a way to learn some of that knowledge. More specifically, the following points are discussed. (1) We introduce a

A great challenge in using any planning system to solve real-world problems is the difficulty of acquiring the domain knowledge that the system will need. We present a way to address part of this problem, in the context of Hierarchical Task Network (HTN) planning, by having the planning system

Abstract. Flexible support for crisis management can definitely be improved by making use of advanced planning capabilities. However, the complexity of the underlying domain often causes intractable efforts in modeling the domain as well as a huge search space to be explored by the system. A way