Received: from turtle.mcc.com by sunscreen.mcc.com (4.1/isd-other_921116_15:19) id AA12205; Wed, 13 Jan 93 04:21:08 CST Received: from venera.isi.edu by turtle.mcc.com (4.1/isd-master_921116_15:19) id AA12609; Wed, 13 Jan 93 04:21:05 CST Received: from isd9.isi.edu by venera.isi.edu (5.65c/5.65+local-7) id <AA05012>; Wed, 13 Jan 1993 02:09:29 -0800 Date: Wed, 13 Jan 1993 01:55:50 -0800 Posted-Date: Wed, 13 Jan 1993 01:55:50 -0800 Received: from by isd9.isi.edu (5.65c/4.0.3-4) id <AA05150>; Wed, 13 Jan 1993 01:55:50 -0800 Message-Id: <9301130941.AA13330@ns3.trl.ibm.com> Comment: SRKB Distribution List Originator: srkb-list@isi.edu Errors-To: neches@isi.edu Reply-To: <HORI@trl.vnet.ibm.com> Sender: srkb-list@isi.edu Version: 5.5 -- Copyright (c) 1991/92, Anastasios Kotsikonas From: Masahiro HORI <HORI@trl.vnet.ibm.com> To: Multiple recipients of list <srkb-list@isi.edu> Subject: [planning & scheduling] the first announcement
<<< SRKB subgroup: knowledge sharing for planning and scheduling >>>
As a special interest subgroup of SRKB phase II activity, we are looking for ways to facilitate the sharing and reuse of knowledge used in planning and scheduling. Our long-term goal is to enable libraries of formally represented, sharable knowledge. Specifically, we are going to explore representation primitives, which will be a basis for developing tools that share models and exchange knowledge at run time. Since scheduling and planning tasks are found in a variety of application domains such as manufacturing, transportation, and manning, it should be possible to share models of domains and problem-solving processes. Thus, our challenge here is to devise a sharable basis for those knowledge representations, appropriately abstracting activities in particular applications.
One of the characteristic features of planning and scheduling is representation of time. Although the ontologies for temporal intervals and relations are rather generic, they will be a good starting point for this subgroup's discussion. Another issue will be the resources that define capacity and capabilities. In the case of production scheduling, a type of machine provides a certain capacity for processing, and an order or an operation may consume an amount of that capacity for a certain period of time. This kind of perspective is relatively common, but further assumptions and commitments must be clarified with respect to the details such as measurement units and representation of attributes associated with resources and consumers, accommodating the differences among representation systems.
This message is an invitation for you to participate in the activities of this working group. In accordance with the general strategy of the SRKB phase II activity, which is to collect, analyze, and experiment with ontologies, a possible road map of this subgroup's activities will include the following:
* Introduce ongoing projects related to this topic - exchange of short descriptions by email - further exchange of papers
* Discuss similarities and differences in those projects - with examples of time, resources ... - clarifying assumptions about the expected scope
* Collect several sample planning and scheduling tasks to be described by using ontologies - various testbed examples such as trivial ones, moderate ones, and real cases.
Of course, the road map is not restricted to the one above, but can change to accommodate participants' interests. Please note that this working group activity is not intended to establish a standard for knowledge representation in planning and scheduling. One of the main objectives is to capture the rationale underlying the design of related ontologies. Thus, it is feasible that various ontologies coexist, all more or less reflecting their own design decisions. This pose an important research issue that is to accommodate modularized ontologies, clarifying the assumptions and commitments associated with those reusable modules. Ultimately, we plan to conduct a small experiment on translatability among ontologies. Those ontologies may include ones proposed by other special interest subgroups, since some of them may be interrelated. The results will be more practical if subgroups collaborate in appropriate areas.
If you are interested in participating, please contact: Masahiro Hori <hori@trl.vnet.ibm.com> or Donald McKay <mckay@vfl.paramax.com>.
CURRENT PROJECTS IN KNOWLEDGE SHARING FOR PLANNING AND SCHEDULING
At least three current projects are associated with this special interest subgroup. We would like to call for more related projects.
One is the DARPA/Rome Laboratory Planning and Scheduling Initiative (DRPI). DRPI is currently supporting a group of 30 or so researchers in the fields of Planning, Scheduling, Knowledge Representation, Case-based Reasoning, Decision Theory, and Database Management with the objective to build integrated, cooperative knowledge based systems. The initiative is organized around a 12 to 18 month cycle of Integrated Feasibility Demonstrations (IFD) and a 4 to 6 month schedule of Technology Integration Experiments (TIE). Each IFD must demonstrate a significant contribution toward solving a critical problem in the domain of Joint Operations Planning as illustrated by problems posed in planning operations, communications, and transportation in Desert Shield/Desert Storm. The TIEs are focused on demonstrating system interoperability at a smaller scale. Over the past two years, the DRPI Knowledge Representation and Architecture Issue Working Group has been guiding the development of a knowledge specification language and system infrastructure to support these cooperative systems. The Knowledge Representation Specification Language (KRSL) is the results. KRSL outlines an ontology for representing time, measurement, objects and concepts, and planning primitives. A shared domain onotology for Joint Operations Planning is being developed in the the KRSL language. (For more information on KRSL contact Nancy Lehrer, nlehrer@isx.com)
The second is the MULTIS project, which has been conducted at Osaka University since 1987. Major efforts have been devoted to development of a task analysis interview system for a general class of scheduling tasks, though the methodology employed is not restricted to scheduling. In the course of the MULTIS project, a set of two-layered ontologies were identified for representing problem solving engines for scheduling and their use in task analysis interview with domain experts. The higher-level ontology represents human problem solving process at the knowledge level and is used for the task analysis interview where it contributes to filling the conceptual gap between the computer and the domain experts. The lower one consists of a set of abstract programs used as building blocks of problem solving engine. The first version of task ontology for scheduling has been edited. (For more information, please contact Riichiro Mizoguchi <miz@ei.sanken.osaka-u.ac.jp>)
The third is the CAKE project, which has been conducted since 1990. It was started to establish a methodology for configuring problem-solving methods with smaller-grained problem-solving components. A class of scheduling problems is focused on. It is called a job assignment task, which is characterized as a set of four elements: jobs, resources, time range, and constraints. The task can be described as assigning all given jobs to the available resources within a specific time range, while satisfying various constraints. Two kinds of ontology are being designed: one is a task ontology for problem specification; the other is a problem-solving ontology for representing the problem-solving processes. These ontologies are defined in KIF and Ontolingua. (For more information contact Masahiro Hori <hori@trl.vnet.ibm.com>) -------------