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{{Short description|Military planning system}}
▲{{Close paraphrasing|date=June 2025}}
'''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="
https://www.modsimworld.org/papers/2016/Training_Effectiveness_Evaluation_of_Lightweight_Game-based_Constructive_Simulation.pdf</ref><ref name="
== 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=
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
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)
In 2000-2002, DARPA applied CADET in the program titled Command Post of the Future ([[Command Post of the Future|CPoF]]) as a tool to
▲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 through 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=
▲From 1996 through 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 ==
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 [[
CADET software resided on a laptop computer. Using the computer, the staff officers entered the input to CADET, or alternatively this input arrived
https://apps.dtic.mil/sti/pdfs/ADA379957.pdf
# Order of Battle, i.e., the units constituting the friendly brigade and the enemy units participating in the battle, and their various characteristics;
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# digital map of the region where the battle was to take place, including the digital description of significant features such as locations of friendly and enemy units, roads, assembly areas, objectives, and axes of attacks.
Taking this input, CADET automatically performed the following tasks (not sequentially):<ref name=
* Planning and scheduling the
* Allocating tasks to
* Assigning suitable locations and routes
* Estimating
* Predicting enemy actions or reactions.
CADET produced the following outputs:<ref name=
# Synchronization matrix, directly editable and printable; synchronization matrix is a kind of Gantt chart that shows assignments of activities to units, to locations/routes and to time periods
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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 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.<ref name=
Although similar to hierarchical-task-network planning algorithm, CADET’s algorithm includes elements of adversarial reasoning. After adding a subtask, the algorithm uses rules to determine the enemy’s probable actions and reactions as well as friendly counteractions This approximated the action-reaction-counteraction technique of manual wargaming used by the United States Army.<ref name=
When a task involves movements of a unit, the algorithm performs routing, i.e., finds a route for the movement that minimizes the time required for the movement as well as exposure to the enemy attacks.<ref name=
Each added tasks (subtask) normally requires a unit which would execute the task, and a time period when the task would be executed. Therefore, when a certain number of subtasks is added by the planning process, the algorithm also performs the allocation of the newly added subtasks to units and to time periods (i.e., scheduling). allocation and scheduling of tasks relies on both ___domain-specific and constraint-guided heuristics.<ref name=
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=
The algorithm continually interleaves incremental steps of planning, routing, scheduling, and attrition and consumption estimates.<ref name=
▲The algorithm continually interleaves incremental steps of planning, routing, scheduling, and attrition and consumption estimates.<ref name=“Kott-2005-Building” />
== Evaluation ==
Two evaluation experiments are described in literature. The first experiment called ICCES took three days.
The second experiment was reminiscent of [[Turing test]]. The experiment involved one user, nine judges (active-duty officers, mainly colonels and lieutenant colonels), and five scenarios obtained from several US Army exercises. For each scenario, experimenters obtained synchronization matrices that were produced in earlier exercises, typically by a team of four to five officers in three to four hours,
== Legacy ==
CADET served as “...an example of how even relatively basic AI systems can potentially affect the implementation of IHL during the military decision-making process.”<ref name=
In early 2000s, CADET influenced the DARPA RAID program (started 2004).<ref name=
▲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 ==
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 name=
== References ==
{{reflist}}
[[Category:Artificial intelligence engineering]]
[[Category:Automated planning and scheduling]]
[[Category:Command and control]]
[[Category:Military exercises and wargames]]
[[Category:Military plans]]
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