Course of Action Display and Evaluation Tool: Difference between revisions

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'''Course of Action Display and Evaluation Tool''' (CADET) was a research program, and the eponymous prototype software system, that applied knowledge-based techniques of Artificial Intelligence to the problem of battle planning. CADET was also known as Course of Action Display and Elaboration Tool.<ref name="Rasch-2003-Incorporating">Rasch, Robert, Alexander Kott, and Kenneth D. Forbus. "Incorporating AI into military decision making: an experiment." IEEE Intelligent Systems 18.4 (2003) pp. 18-26.</ref>

It was considered an early example of such systems<ref name="“Schuster-2018-When”">Schuster, E. (2018). When Something Has to Give: The Intersection of Artificial Intelligence, Military Decision-Making and International Humanitarian Law. Thesis, Lund University, Sweden, 2018</ref> and was funded by the United States Army and by the [[Defense Advanced Research Projects Agency]] (DARPA). CADET influenced a later DARPA program called RAID<ref name="“Kott-2005-Real-time”">Kott, A., Real-time Adversarial Reasoning and Decision-making Program, Proceedings of the 10th ICCRT Symposium, McLean, Virginia, USA,13–16 June 2005. Online at http://www.dodccrp.org/events/10th_ICCRTS/CD/presentations/170.pdf </ref> which in turn produced a technology adopted by the United States Army and the United States Marine Corps.<ref name="“Stevens-2016-Training”">Stevens, Jonathan, Ms Latika Eifert, Stephen R. Serge, and Sean Mondesire. "Training Effectiveness Evaluation of Lightweight Game-based Constructive Simulation." Proceedings of the ModSim Conference, 2016. Online at

Course of Action Display and Evaluation Tool (CADET)

https://www.modsimworld.org/papers/2016/Training_Effectiveness_Evaluation_of_Lightweight_Game-based_Constructive_Simulation.pdf</ref> <ref name="”BAE”">{{cite web | url=https://militaryembedded.com/ai/machine-learning/bae-systems-prototype-selected-for-us-marine-corps-wargaming-and-analysis-center | title=BAE Systems' prototype selected for U.S. Marine Corps Wargaming and Analysis Center - Military Embedded Systems }}</ref>

Course of Action Display and Evaluation Tool (CADET) was a research program, and the eponymous prototype software system, that applied knowledge-based techniques of Artificial Intelligence to the problem of battle planning. CADET was also known as Course of Action Display and Elaboration Tool.<ref name="Rasch-2003-Incorporating">Rasch, Robert, Alexander Kott, and Kenneth D. Forbus. "Incorporating AI into military decision making: an experiment." IEEE Intelligent Systems 18.4 (2003) pp. 18-26.</ref>

It was considered an early example of such systems<ref name=“Schuster-2018-When”>Schuster, E. (2018). When Something Has to Give: The Intersection of Artificial Intelligence, Military Decision-Making and International Humanitarian Law. Thesis, Lund University, Sweden, 2018</ref> and was funded by the United States Army and by the [[Defense Advanced Research Projects Agency]] (DARPA). CADET influenced a later DARPA program called RAID<ref name=“Kott-2005-Real-time”>Kott, A., Real-time Adversarial Reasoning and Decision-making Program, Proceedings of the 10th ICCRT Symposium, McLean, Virginia, USA,13–16 June 2005. Online at http://www.dodccrp.org/events/10th_ICCRTS/CD/presentations/170.pdf </ref> which in turn produced a technology adopted by the United States Army and the United States Marine Corps.<ref name=“Stevens-2016-Training”>Stevens, Jonathan, Ms Latika Eifert, Stephen R. Serge, and Sean Mondesire. "Training Effectiveness Evaluation of Lightweight Game-based Constructive Simulation." Proceedings of the ModSim Conference, 2016. Online at

https://www.modsimworld.org/papers/2016/Training_Effectiveness_Evaluation_of_Lightweight_Game-based_Constructive_Simulation.pdf</ref> <ref name=”BAE”>{{cite web | url=https://militaryembedded.com/ai/machine-learning/bae-systems-prototype-selected-for-us-marine-corps-wargaming-and-analysis-center | title=BAE Systems' prototype selected for U.S. Marine Corps Wargaming and Analysis Center - Military Embedded Systems }}</ref>

== History ==

The development of Course of Action Display and Evaluation Tool (CADET) began in 1996, at the Carnegie Group, Inc.,<ref>Phillips, Eve Marie. If it works, it's not AI: a commercial look at artificial intelligence startups. Dissertation, Massachusetts Institute of Technology, 1999.</ref> Pittsburgh PA, funded under the [[Small Business Innovation Research]] (SBIR) program. The goal of the first phase SBIR project was to produce “...a live storyboard of [Course of Action] COA development, wargaming, animation, and assessment.”<ref name=“Ground-2002-Knowledge”>Ground, Larry, Alexander Kott, and Ray Budd. A knowledge-based tool for planning of military operations: The coalition perspective. Technical Report, BBN Technologies, Pittsburgh PA, 2002. Online at https://apps.dtic.mil/sti/pdfs/ADA402533.pdf</ref>

In 1997, the United States Army awarded the Carnegie Group Inc. $750K for SBIR Phase II. The intent was to develop “...a war-gaming modeling and analysis Decision Support System (DSS), … CADET will consist of a combination of Knowledge-Based and decision analytic tools and technologies to provide fast nimble COA war-gaming modeling, simulation, and animation under direct control of the commander and staff. ...Phase II will result in an operations prototype (OP) suitable for use and evaluation in field exercises. A fully functional COA analyzer/wargaming DSS for the commander and staff would be developed in Phase III.”<ref>{{cite web | url=https://www.sbir.gov/awards/28447 | title=Award &#124; SBIR }}</ref>

In 2000, CADET was integrated and experimentally evaluated within the framework of the Integrated Course of Action Critiquing and Elaboration System (ICCES) experiment, conducted by the Battle Command Battle Laboratory – Leavenworth (BCBL-L) as a result of a TRADOC sponsored Concept Experimentation Program (CEP).<ref name=“Rasch-2002-AI”>Rasch, Robert, Alexander Kott, and Kenneth D. Forbus. "AI on the battlefield: An experimental exploration." In AAAI/IAAI, pp. 906-912. 2002. Online at https://www.qrg.northwestern.edu/papers/Files/AI_in_MDMP_IAAI02.pdf</ref>

In 2000-2002, DARPA applied CADET in its Command Post of the Future ([[Command Post of the Future|CPoF]]) program

as a tool to provide a maneuver course of action. Under the umbrella of the CPoF program, CADET was integrated with the FOX GA system to provide a detailed planner, coupled with COA generation capability. In the same period, Battle Command Battle Lab-Huachuca (BCBL-H) integrated CADET with All Source Analysis System-Light (ASAS-L) to provide a planner for intelligence assets and to wargame enemy COAs against friendly COAs.<ref name=“Ground-2002-Knowledge” /> <ref name=“Ruda-2001-Distributed”>Ruda, Harald, Janet Burge, Peter Aykroyd, Jeffrey Sander, Dennis Okon, and Greg L. Zacharias. "Distributed course-of-action planning using genetic algorithms, XML, and JMS." In Battlespace Digitization and Network-Centric Warfare, vol. 4396, pp. 260-269. SPIE, 2001. </ref>

From 1996 thruthrough 2002, work on CADET was performed by the Carnegie Group, Inc., and supported by funding from the US Army [[CECOM]] (CADET SBIR Phase I, CADET SBIR Phase II and CADET Enhancements); DARPA (Command Post of the Future); and [[United States Army Training and Doctrine Command|TRADOC]] BCBL-H.<ref name=“Kott-2002-Toward”>Kott, Alexander, Larry Ground, Ray Budd, Lakshmi Rebbapragada, and John Langston. "Toward practical knowledge-based tools for battle planning and scheduling." In Proceedings of AAAI/IAAI, pp. 894-899. 2002. Online at

From 1996 thru 2002, work on CADET was performed by the Carnegie Group, Inc., and supported by funding from the US Army [[CECOM]] (CADET SBIR Phase I, CADET SBIR Phase II and CADET Enhancements); DARPA (Command Post of the Future); and [[United States Army Training and Doctrine Command|TRADOC]] BCBL-H.<ref name=“Kott-2002-Toward”>Kott, Alexander, Larry Ground, Ray Budd, Lakshmi Rebbapragada, and John Langston. "Toward practical knowledge-based tools for battle planning and scheduling." In Proceedings of AAAI/IAAI, pp. 894-899. 2002. Online at

https://www.aaai.org/Papers/IAAI/2002/IAAI02-132.pdf </ref>

== Operation ==

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* Estimating friendly and enemy battle losses (attrition), and consumption of resources (e.g., fuel and ammunition)

* Predicting enemy actions or reactions.

CADET produced the following outputs:<ref name=“Ground-2000-CADET” />

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# Textual Operation Plan ([[OPLAN]]) draft

# E-mail messages with attachments: XML and text versions of OPLAN

== Design ==

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A tasks may also require expenditures of fuel and ammunition. If the tasks involves engagement with the enemy, the performing units will experience lossesof personnel and weapon systems (attrition). CADET’s algorithm includes estimates of consumption of different types of consumables, and also attrition. Depending on the degree of attrition and consumption, CADET adds tasks that are needed to refuel or reconstitute the units.<ref name=“Ground-2000-CADET” />

The algorithm continually interleaves incremental steps of planning, routing, scheduling, and attrition and consumption estimates.<ref name=“Kott-2005-Building” />

== Evaluation ==

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In early 2000s, CADET influenced the DARPA RAID program (started 2004).<ref name=“Kott-2005-Real-time” /> The RAID program in turn produced a technology adopted by the Army and the United Sattes Marine Corps.<ref name=“Stevens-2016-Training” /> <ref name=”BAE” />

== Criticisms ==