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 mixed-initiative 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 Domai
The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprint...
The paper raises some issues relating to the engineering of domain models for automated planning. It...
Automated planning is a prominent Artificial Intelligence challenge, as well as being a common capab...
We describe a Graphical Interface for Planning with Objects called GIPO that has been built to inves...
Knowledge engineering in AI planning is the process that deals with the acquisition, validation and ...
Formulating knowledge for use in AI Planning engines is currently some-thing of an ad-hoc process, w...
The process of how knowledge is acquired and formulated in knowledge-intensive AI is difficult for a...
AI planning engines require detailed specifications of dynamic knowledge of the domain in which the...
In this paper an object-centric perspective on planning domain definition is presented along with an...
Within the field 'artificial intelligence' are many disciplines, one of which is planning. Planning ...
AbstractIn this paper we discuss techniques for representing and organizing knowledge that enable a ...
Teaching of knowledge-intensive AI is particularly hard as the process of how knowledge is acquired ...
This paper argues that AI planning is a technology ripe for use on real world problems as shown by a...
Constructing a planner for a particular application is a difficult job, for which little concrete su...
A great deal of emphasis in classical AI planning research has been placed on search-control issues ...
The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprint...
The paper raises some issues relating to the engineering of domain models for automated planning. It...
Automated planning is a prominent Artificial Intelligence challenge, as well as being a common capab...
We describe a Graphical Interface for Planning with Objects called GIPO that has been built to inves...
Knowledge engineering in AI planning is the process that deals with the acquisition, validation and ...
Formulating knowledge for use in AI Planning engines is currently some-thing of an ad-hoc process, w...
The process of how knowledge is acquired and formulated in knowledge-intensive AI is difficult for a...
AI planning engines require detailed specifications of dynamic knowledge of the domain in which the...
In this paper an object-centric perspective on planning domain definition is presented along with an...
Within the field 'artificial intelligence' are many disciplines, one of which is planning. Planning ...
AbstractIn this paper we discuss techniques for representing and organizing knowledge that enable a ...
Teaching of knowledge-intensive AI is particularly hard as the process of how knowledge is acquired ...
This paper argues that AI planning is a technology ripe for use on real world problems as shown by a...
Constructing a planner for a particular application is a difficult job, for which little concrete su...
A great deal of emphasis in classical AI planning research has been placed on search-control issues ...
The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprint...
The paper raises some issues relating to the engineering of domain models for automated planning. It...
Automated planning is a prominent Artificial Intelligence challenge, as well as being a common capab...