Abstract
Use of knowledge-based decision aids can help alleviate the challenges of planning complex operations. We describe a knowledge-based tool capable of translating a high-level concept for a tactical military operation into a fully detailed, actionable plan, producing automatically (or with human guidance) plans with realistic degree of detail and complexity. Tight interleaving of planning, adversary estimates, scheduling, routing, attrition and consumption processes comprise the computational approach of this tool. Although originally developed for Army large-unit operations, the technology is generic and also applies to a number of other domains, particularly in critical situations requiring detailed planning within a constrained period of time. In this paper, we focus particularly on the engineering tradeoffs in the design of the tool. An experimental comparative evaluation indicated that the tool's performance compared favorably with human planners.
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Alexander Kott is a Program Manager at Defense Advanced Research Projects Agency (DARPA). While performing the research described in this paper, he was the Director of R&D at Carnegie Group, Inc., and a Technical Director at BBN Technologies in Pittsburgh, PA. His work included development of algorithms and decision aids for dealing with dynamic planning and scheduling in constrained, uncertain and adversarial environments, and research in dynamic distributed decision-making systems, such as in military command and control. He earned his PhD from the University of Pittsburgh where he explored the use AI techniques for innovative design of systems. He can be reached at DARPA, 3701 N Fairfax Drive, Arlington, VA, 22203.
Raymond Budd is a member of the technical staff at BBN Technologies. His areas of interest include knowledge representations, knowledge engineering, and planning and scheduling. He received a BS in computer science from the University of Pittsburgh. Contact him at BBN Technologies 1300 N. 17th Street, Suite 400, Arlington, VA 22209.
Larry Ground is a senior analyst with Green River Associates, Inc. His research interests include development of tools for analysis and decision support of Army maneuver and logistics planning. Retired from the US Army as a Lieutenant Colonel, he served in a variety of command and staff positions and taught at the US Army Command and General Staff College. He is a Certified Professional Logistician by the International Society of Logistics. Contact him at Green River Associates, Inc., Fredericksburg, VA.
Lakshmi Rebbapragada is a senior computer engineer at US Army CECOM Research, Development and Engineering Center (RDEC). Her research interests include application of advanced technologies to tactical planning, execution-based replanning, VA Standards for Ontology based Knowledge sharing re-use, and Network Centric Infrastructure for Command and Control. She is a member of the IEEE Standard Upper Ontology (SUO) Working Group. She has a Ph.D in High Energy Physics from Bristol University U.K. She can be contacted at PM UA NSI Battle Command, Bldg. 2405, Ft. Monmouth, NJ 07703. John Langston is a senior analyst with Austin Information Systems. He served in a variety of command and staff positions in the US Army, including extensive combat experience in the Republic of Vietnam. Retired as a Lieutenant Colonel, he is widely recognized for his extensive research and knowledge in the areas of military leadership and decision making and has contributed significantly to the development of automated battle planning tools. Contact him at Austin Information Systems, Whispering Woods Cove, Parkville, MO 64152.
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Kott, A., Budd, R., Ground, L. et al. Building a Tool for Battle Planning: Challenges, Tradeoffs, and Experimental Findings. Appl Intell 23, 165–189 (2005). https://doi.org/10.1007/s10489-005-4606-z
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DOI: https://doi.org/10.1007/s10489-005-4606-z