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{{Short description|Early technology for military planning system}}
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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): 18-26.</ref> It was considered an early example of such systems<ref>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>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>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>
▲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): 18-26.</ref> It was considered an early example of such systems<ref>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>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>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>{{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., 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>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 | 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>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, 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>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>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> <ref>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 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>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 ==
CADET operation is described in several publications.<ref name="Rasch-2003-Incorporating" /> <ref>Ground, Larry, and Alex Kott. CADET Enhancements. Technical Report. Logica Carnegie Group, Pittsburgh PA, 2000. Online at
https://apps.dtic.mil/sti/pdfs/ADA379957.pdf </ref>
CADET was intended to be used by the [[Staff (military)|staff]] of the United States Army [[Brigade combat team|Brigade]], within the [[Military Decision Making Process]] (MDMP). In particular, CADET helped produce, automatically or semi-automatically, the products generated within the step of MDMP called Course of Action (COA) Development and the following step of MDMP called COA Analysis and [[Military_wargaming|Wargaming]].
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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>Ground, Larry, and Alex Kott. CADET Enhancements. Technical Report. Logica Carnegie Group, Pittsburgh PA, 2000. Online at
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# XML formally-encoded plan
# Textual Operation Plan ([[OPLAN]]) draft
# E-mail messages with attachments: XML and text versions of OPLAN
== Design ==
The algorithms of CADET are described in several publications.<ref>Ground, Larry, and Alex Kott. CADET Enhancements. Technical Report. Logica Carnegie Group, Pittsburgh PA, 2000. Online at
https://apps.dtic.mil/sti/pdfs/ADA379957.pdf </ref>
The core algorithm is a planning algorithm where CADET uses a knowledge-based approach of the hierarchical-task-network type. Each task class is associated with a model of more detailed subtasks that should be performed in order to accomplish the higher-level task. Algorithms selected (heuristically) a task and then decomposes it into subtasks.
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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.
The algorithm continually interleaves incremental steps of planning, routing, scheduling, and attrition and consumption estimates.
== Evaluation ==
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In early 2000s, CADET influenced the DARPA RAID program (started 2004).<ref>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> The RAID program in turn produced a technology adopted by the Army and the United Sattes Marine Corps.<ref>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>
== Criticisms ==
It was argued that in the CADET approach “...the decision-making of the process is obscured, and unaccountable,” and optimality of the planning process is traded for speed.<ref>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>
== References ==
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