A tool-supported approach to engineering HTN planning models

Proceedings of the International Conference on Knowledge Engineering and Ontology Development

2014

Abstract:This paper introduces the Knowledge Engineering Web Interface (KEWI) which primarily aims to be used for modelling automated planning tasks in a semi-formal framework. The conceptual model used to represent the declarative and procedural knowledge in KEWI is described formally. The model consists of three layers: a rich ontology, a model of basic actions, and more complex methods. It is this structured conceptual model based on the rich ontology that facilitates knowledge engineering. The focus of this paper is to show how the central knowledge model used in KEWI differs from a model directly encoded in PDDL, the language accepted by most existing planning engines. Specifically, the rich ontology enables a more concise and natural style of representation. For operational use, KEWI automatically generates PDDL. Initial experiments show that the generated PDDL can be processed by a planner without incurring significant drawbacks.

Section: Related Workmentioning

confidence: 99%

KEWI - A Knowledge Engineering Tool for Modelling AI Planning Tasks

Wickler

Chrpa

Proceedings of the International Conference on Knowledge Engineering and Ontology Development

2014

“…GIPO provides editors and tools to support HTN planning as expressed in the OCL h language (McCluskey & Kitchin, 1998). In brief, GIPO allows the definition of methods which are actions that can be specified in terms of a composition of actions as defined for classical planning.…”

Section: Htn Planningmentioning

confidence: 99%

Planning domain definition using GIPO

Simpson

Kitchin

The Knowledge Engineering Review

2007

In this paper an object-centric perspective on planning domain definition is presented along with an overview of GIPO (graphical interface for planning with objects), a supporting tools environment. It is argued that the object-centric view assists the domain developer in conceptualizing the domain's structure, and we show how GIPO enables the developer to capture that conceptualization at an appropriate and matching conceptual level. GIPO is an experimental environment which provides a platform for exploring and demonstrating the range and scope of tools required to support the knowledge engineering aspects of creating and validating planning systems, both for classical pre-condition planning and hierarchical planning. GIPO embodies the objectcentric view, leading to a range of benefits typically associated with object-oriented methods in other fields of software engineering such as highly visual development methods, code reuse and efficient, reliable development.

“…The language family used is OCL h [17,15]. OCL h a structured, formal language for the capture of both classical and hierarchical, HTN-like domains.…”

Section: Underlying Representation Formalismmentioning

confidence: 99%

Knowledge Formulation for AI Planning

Engineering Knowledge in the Age of the Semantic Web

Simpson

2004

Abstract. In this paper we present an overview of the principle components of GIPO, an environment to support knowledge acquisition for AI Planning. GIPO assists in the knowledge formulation of planning domains, and in prototyping planning problems within these domains. GIPO features mixedinitiative components such as generic type composition, an operator induction facility, and various plan animation and validation tools. We outline the basis of the main tools, and show how an engineer might use them to formulate a domain model. Throughout the paper we illustrate the formulation process using the Hiking Domain.