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OZONE
About
This research builds
from
our
previous work in constraint-based scheduling and focuses on two key
obstacles
to the development and application of intelligent systems in
large-scale
planning and scheduling domains such as manufacturing management and
crisis-action
logisitics planning:
- Current
systems do not
effectively
support user tasks and requirements - They force users to operate on
their
terms, provide no guidance in understanding, diagnosing and improving
results,
and do not support the iterative, evolving process of problem
understanding,
requirements determination, conflict resolution and solution refinement
that is inherent in large-scale, multi-agent problem solving.
- Current
application
building
efforts
are difficult, costly and time consuming tasks. The power of
knowledge-based
planning and scheduling technologies, i.e., their ability to encode and
productively exploit high-fidelity models of the target environment and
domain-specific heuristics, is also their "Achilles' heel" from a
system
development perspective.
Approach
We are developing
theories,
techniques
and software architectures that address these problems, enabling both
flexible
collaborative problem solving between user and system, and flexible
reconfiguration
of system functionality to accommodate new domains and/or domain
requirements.
Our approach to mixed-initiative systems properly recognizes scheduling
for what it is in most practical domains: an iterative process of
"getting
the constraints right" in which humans always have strategic,
big-picture
decision-making expertise and knowledge to contribute but are unable to
effectively cope with the complexity of detailed solution development.
We are developing a collaborative scheduling framework based on this
process
viewpoint, where the user visualizes and manipulates solutions from
comprehensible,
aggregate perspectives, and the system incrementally manages the
details
of user changes in accordance with communicated goals and expectations.
Our approach to scheduling system architecture builds from object
technology
concepts. We are developing a general "ontology" of scheduling concepts
to enable application in different domains and allow integration with
other,
complementary problem solving and information processing services. Our
broader goal is a planning and scheduling "tool box", an application
construction
environment which couples a system configuration infra-structure with
expandable
libraries of functional componentry.
Application
Context
and
Software
Technologies
The dominant
application
focus
of this work, funded under the ARPA/Rome Laboratories Planning
Initiative,
is military crisis-action deployment scheduling. This has led to
development
of the DITOPS
scheduling system. DITOPS combines the use of hierarchical domain
models
and solution visualizations with reactive, constraint-based scheduling
techniques to provide advanced capabilities for generating, analyzing,
manipulating and improving deployment schedules. At the same time,
DITOPS
has been designed for reconfigurability; the supporting OZONE
scheduling
infra-structure provides a rich class library of modeling and
scheduling
services that make the system readily applicable to other problem
domains.
Recent
Publications
- S.F. Smith, O.
Lassila
and M.
Becker, Configurable,
Mixed-Initiative Systems for Planning and Scheduling, in
Advanced
Planning Technology, (ed. A. Tate), AAAI Press, Menlo Park, CA, May,
1996.
- M. Becker, and
S.F.
Smith, "Using
DITOPS as a Tool for Mixed-Initiative Schedule Improvement"
(This
is a TAR file with the gzipped version of the paper. The post-script
file
has been split into 6 parts because of its size. Download the file, 1M,
untar with "tar xvf ditops-demo.tar", goto the compressed directory,
"gunzip
ditops-demo-ps*").
- Smith, S.F.
and M.
Becker, "An
Ontology for Constructing Scheduling Systems", to appear in Working
Notes of 1997 AAAI Symposium on Ontological Engineering, Stanford,
CA, March, 1997 (AAAI Press).
- O. Lassila, M.
Becker
and
S.F. Smith, "An
Exploratory Prototype for Air Medical Evacuation Re-Planning", CMU
Robotics Institute Technical Report CMU-RI-TR-96-03, January, 1996.
- S.F. Smith, "Reactive
Scheduling Systems", in Intelligent Scheduling Systems,
(eds.
Brown & Scherer), Kluwer Publishing, 1995.
- M. Burstien,
R. Shantz,
M.
Bienkowski,
M.desJardin and S.F. Smith, "The Arpa/Rome Laboratory Common
Prototyping
Environment: A Framework for Software Technology Integration,
Evaluation
and Transition", IEEE Expert, Vol. 10, No. 1, February 1995.
- S.F.Smith and
O.Lassila, Toward
the Development of Mixed-Initiative Scheduling systems,
ARPA-Rome
Laboratory Planning Initiative Workshop, Tucson (AZ), 1994.
- O.Lassila and
S.F.Smith, Constructing
Flexible Scheduling Systems for Decision Support, Proceedings
1994
Finnish AI Symposium, Turku (Finland), August 1994.
- O.Lassila and
S.F.Smith, Flexible,
Constraint-Based Tools for Complex Scheduling Applications,
IEEE
4th Annual Dual-Use Technologies & Applications Conference, Utica
(NY),
1994.
- S.F. Smith, O.
Lassila
and M.
Becker,
"Configurable Planning and Scheduling Systems", AI*IA Notizie
(Quarterly
Publication of the Artificial Intelligence Italian Association),
Special
Issue on Aspects of Planning Research, Vol.9, No. 1, March, 1996, pp.
27-32.
- S.F. Smith, O.
Lassila
and M.
Becker,
"A Scheduling Ontology: Informal Concept Descriptions", ICLL Working
Paper,
January, 1996.
- S.F.Smith and
O.Lassila, Configurable
Systems for Reactive Production Management, IFIP Transactions
B-15,
Elsevier Science B.V., 1994.
- S.F.Smith and
K.P.
Sycara, Flexible
Coordination in Resource-Constrained Domains, Technical Report
CMU-RI-TR-93-17,
The Robotics Institute, Carnegie Mellon University, December, 1993.
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