In recent years research in the planning community has moved increasingly towards application of planners to realistic problems involving both time and many types of resources. For example, interest in planning demonstrated by the space research community has inspired work in observation scheduling, planetary rover exploration and spacecraft control domains. Other temporal and resource-intensive domains including logistics planning, plant control and manufacturing have also helped to focus the community on the modelling and reasoning issues that must be confronted to make planning technology meet the challenges of application.

The International Planning Competitions have acted as an important motivating force behind the progress that has been made in planning since 1998. The third competition (held in 2002) set the planning community the challenge of handling time and numeric resources. This necessitated the development of a modelling language capable of expressing temporal and numeric properties of planning domains. In this paper we describe the language, PDDL2.1, that was used in the competition. We describe the syntax of the language, its formal semantics and the validation of concurrent plans. We observe that PDDL2.1 has considerable modelling power -- exceeding the capabilities of current planning technology -- and presents a number of important challenges to the research community.

/pdf/pddl2-1-an-extension-to-pddl-for-expressing-temporal-1u955z1r8x.pdf

PDDL2.1: an extension to PDDL for expressing temporal planning domains

Service interface description languages such as WSDL, and related standards, are evolving rapidly to provide a foundation for interoperation between Web services. At the same time, Semantic Web service technologies, such as the Ontology Web Language for Services (OWL-S), are developing the means by which services can be given richer semantic specifications. Richer semantics can enable fuller, more flexible automation of service provision and use, and support the construction of more powerful tools and methodologies. Both sets of technologies can benefit from complementary uses and cross-fertilization of ideas. This paper shows how to use OWL-S in conjunction with Web service standards, and explains and illustrates the value added by the semantics expressed in OWL-S.

https://eprints.soton.ac.uk/263000/1/OWL-S-SWSWPC2004-final.pdf

Bringing semantics to web services: the OWL-S approach

The SHOP2 planning system received one of the awards for distinguished performance in the 2002 International Planning Competition. This paper describes the features of SHOP2 which enabled it to excel in the competition, especially those aspects of SHOP2 that deal with temporal and metric planning domains.

/pdf/shop2-an-htn-planning-system-20n5kqaph4.pdf

SHOP2: an HTN planning system

https://www.cs.umd.edu/~nau/papers/sirin2004htn.pdf

HTN planning for Web Service composition using SHOP2

Automated discovery, interaction and composition of Semantic Web services

SHOP (Simple Hierarchical Ordered Planner) is a domain-independent HTN planning system with the following characteristics. • SHOP plans for tasks in the same order that they will later be executed. This avoids some goal-interaction issues that arise in other HTN planners, so that the planning algorithm is relatively simple. • Since SHOP knows the complete world-state at each step of the planning process, it can use highly expressive domain representations. For example, it can do planning problems that require complex numeric computations. • In our tests, SHOP was several orders of magnitude faster man Blackbox and several times faster than TLpian, even though SHOP is coded in Lisp and the other planners are coded in C.

/pdf/shop-simple-hierarchical-ordered-planner-1lk5tmfr3d.pdf

SHOP: Simple Hierarchical Ordered Planner

One of the more controversial recent planning algorithms is the SHOP algorithm, an HTN planning algorithm that plans for tasks in the same order that they are to be executed. SHOP can use domaindependent knowledge to generate plans very quickly, but it can be difficult to write good knowledge bases for SHOP.

Our hypothesis is that this difficulty is because SHOP's total-ordering requirement for the subtasks of its methods is more restrictive than it needs to be. To examine this hypothesis, we have developed a new HTN planning algorithm called SHOP2. Like SHOP, SHOP2 is sound and complete, and it constructs plans in the same order that they will later be executed. But unlike SHOP, SHOP2 allows the subtasks of each method to be partially ordered.

Our experimental results suggest that in some problem domains, the difficulty of writing SHOP knowledge bases derives from SHOP's total-ordering requirement--and that in such cases, SHOP2 can plan as efficiently as SHOP using knowledge bases simpler than those needed by SHOP.

/pdf/total-order-planning-with-partially-ordered-subtasks-4cfu407tzt.pdf

Total-order planning with partially ordered subtasks

Shop is a hierarchical task network planning algorithm that is provably sound and complete across a large class of planning domains. It plans for tasks in the same order that they will later be executed, and thus, it knows the current world state at each step of the planning process. shop takes advantage of this knowledge by allowing a high degree of expressive power in its knowledge bases. For example, shop's preconditions can include logical inferences, complex numeric computations, and calls to external programs. shop is powerful enough that an implementation of it is being used as an embedded planner in the Naval Research Laboratory's hicap system.

/pdf/the-shop-planning-system-mr68jy1iur.pdf

The Shop Planning System

: SHOP (Simple Hierarchical Ordered Planner) and M-SHOP (Multi-task-list SHOP) are HTN planning algorithms with the following characteristics. SHOP and M-SHOP plan for tasks in the same order that they will later be executed. This avoids some task interaction issues that arise in other HTN planners, making the planning algorithms relatively simple. This also makes it easy to prove soundness and completeness results. Since SHOP and M-SHOP know the complete world-state at each step of the planning process, they can use highly expressive domain representations. For example, they can do planning problems that require Horn-clause inferencing, complex numeric computations, and calls to external programs. In our tests, SHOP and M-SHOP were several orders of magnitude faster than Blackbox, IPP, and UMCP, and were several times as fast as TLplan. The approach is powerful enough to be used in complex real-world planning problems. For example, we are using a Java implementation of SHOP as part of the HICAP plan-authoring system for Noncombatant Evacuation Operations (NEOs). In this paper we describe SHOP and M-SHOP, present soundness and completeness results for them, and compare them experimentally to Blackbox, IPP, TLplan, and UMCP. The results suggest that planners that generate totally ordered plans starting from the initial state can scale up to complex planning problems better than planners that use partially ordered plans.

/pdf/shop-and-m-shop-planning-with-ordered-task-decomposition-1m6e93inqs.pdf

SHOP and M-SHOP: Planning with Ordered Task Decomposition

Keywords: HTN-planning, multi-agents In this paper we describe a formalism for integrating the SHOP HTN planning system with the IMPACT multi-agent environment. Our formalism provides an agentized adaptation of the SHOP planning algorithm that takes advantage of IMPACT's capabilities for interacting with external agents, performing mixed symbolic/numeric computations, and making queries to distributed, heterogeneous information sources (such as arbitrary legacy and/or specialized data structures or external databases). We show that this agentized version of SHOP will preserve soundness and completeness if certain conditions are met.

Yue Cao

Papers

SHOP: Simple Hierarchical Ordered Planner

Total-order planning with partially ordered subtasks

The Shop Planning System

SHOP and M-SHOP: Planning with Ordered Task Decomposition

IMPACTing SHOP: Foundations for integrating HTN Planning andMulti-Agency