Task Based Approach To Planning
Task Based Approach to PlanningJeff AbbottSystems ArchitectCAE USA Professional Services3501 Quadrangle BLVDOrlando, FL, 32817 USA407-745-2605jeff.abbott@cae.comRobert P. GoldmanSenior ScientistSmart Information Flow Technologies211 N. First St., Suite 300Minneapolis, MN 55401 USA612-384-3454rpgoldman@SIFT.infoKeywords: Battle Management Language (BML), Military Standard Definition Language (MSDL), Orders,Task, Missions, Course of ActionABSTRACT: The Task Based Approach to Planning utilizes doctrinal tasks (AUTL, MTP, etc) in context to theplanning cycle represented by the Army’s Military Decision Making Process (MDMP). Receipt of Mission Mission Analysis COA Development COA Analysis (Wargaming) COA Comparison COA Approval Orders ProductionThis paper explores the feasibility of enabling a semi-automated military decision making process across all steps of theMilitary Decision Making Process (MDMP). Automation of these steps depends on successful integration of CGFsystems, JC3IEDM, battle management language represented by collective tasks and their associated measures ofperformance and effectiveness.The approach to automation of the MDMP is to focus on associating command and control aspects of the MDMP to themeasures and decision points of collective tasks. Decision points represent potential branches for future courses ofaction. Measures of collective tasks provide a common means for comparing the future value of each COA branch.Common criteria or measures of effectiveness (MOE), for comparing COA branches at a decision point, are derivedthrough backwards planning. These MOEs represent measures for mission success. The COA (branch) specificmeasures of performance (MOP) are used to evaluate each COA by the common set of MOEs. The decision points areidentified by backwards planning from the final objective to the start of the mission. The decisions to be made are inspecific context to the current situation (METT-TC) and means of accomplishing each COA branch. The measures ofthe decision point’s (DP) objective situation are represented by a METT-TC estimate derived through backwardsplanning. These DP measures are criteria for evaluating the effectiveness of COA options (candidate branches). TheMETT-TC measures of performance resulting from COA analysis (wargaming) are used to generate each COA’s valueor MOE. The DP criteria are used to evaluate and compare the COA options by their respective MOE values. Thecommander is responsible for identifying decision points, the criteria, and weights for assessing MOEs of the options.The COA generation, analysis, and comparison are the focus of the automated MDMP.1IntroductionThe analog steps of COA Analysis and Comparison arecurrently as subjective as they are quantitative. If weassume the Army’s MTP tasks can be modeledcomputationally, those tasks could be used to analyze andassess options just as they are used to analyze and assessthe proficiency of combat elements. If MTP tasks can beused to assess SAF-CGF performance, it must be assumedthat CGF combat elements are proficient in taskperformance. This assumption appears to hold true forSAF-CGF systems developed from task based doctrine,such as OneSAF. What is missing from the SAF-CGFbehaviors is the cognitive ability to perform effectivecommand and control (balance resource means withconstraints of the mission).
1.1Operational ViewThe Task Based Approach to Planning utilizes Armytasks (AUTL, MTP, etc) in context to the planning cyclerepresented by the Army’s Military Decision MakingProcess (MDMP). Figure 1: Operational Planning and theMDMP below depict the relationship of the MDMP todata representations of task based planning.Figure 1: Operational Planning and the MDMPThe steps of COA Analysis and Comparison are bothsubjective as well as quantitative. If we assume theArmy’s MTP tasks can be modeled computationally,those tasks could be used to analyze and assess optionsjust as they are used to analyze and assess the proficiencyof combat elements.1.2Operational to System View MatrixThe Task Based Planning components align very wellwith the steps of the MDMP as shown in Figure 2: TaskBased Planning and the MDMP.to mission objectives. Software agents use tasks andassessments of tasks on the trajectory of the ongoingoperation, to estimate future value (effectiveness) ofavailable options. For example, Lanchester equations andBayesian networks can be used to determine thelikelihood of each option’s success.Options aregenerated automatically or semi-automatically by placinga set of Mission Training Plan (MTP) tasks into a specificsituational METT-TC context. The METT-TC contextprovides for measures of effectiveness which constrainacceptable (effective) performance. The measurements ofperformance (MOPs) are achieved using a Lancaster andBayesian based simulation driven by the currentsituational factors of METT-TC. Each task is evaluatedby the MTP tasks which form templates for assessment ofan option’s effectiveness. Specific MTP tasks are selectedas templates given the AUTL and the unit/elementperforming the task; Infantry Company for example.Task steps flagged in the MTP as leader tasks equate todecision points. Task steps and performance measuresflagged as critical drive commander’s critical informationrequirements (CCIR) that must be measured or estimatedbefore an option can be selected as a viable (feasible)branch of execution. The COA Generator evaluates theMTP task to place the performance measures into theproper METT-TC context. That context represents themeasures of performance for each performance measure.The COA Analyzer evaluates these MOPs based onboundary conditions of the tasks represented as resourceconstraints to include time in order to determine a TPUevaluation. Tasks which are evaluated to Uneffective areeliminated as possible steps for any option. Tasksevaluated to Partially effective are refined by modifyingperformance criteria (measures designated in the order).Tasks evaluated as Totally effective are adopted as part ofthe option. If a complete set of tasks cannot be identifiedas effective for an option that option is trimmed from thetree.Figure 2: Task Based Planning and the MDMPKnowing how components of Task Based Planning relateto the MDMP enables the developer to integrate Armytasks within this context. These tasks are used tocomputationally assess the proficiency of units in theconduct of the tasks. The assumption is that these sametasks can be used to computationally assess the feasibilityof a task’s performance being effective in context to amission or COA.1.3Operational Task Based PlanningThe Task Based concept is an innovative approach tousing the Army’s Universal Task List (AUTL) to supportthe assessment and decision making of ongoing militaryoperations while they are being conducted. The approachis to maintain a state space graph of possible future statesrelated to the potential effectiveness of tasks as they relateFigure 3: Computational Task Based Planning &Analysis
1.4Operational Task Based Planning and theMDMPGiven the task based approach to planning can be used togenerate options and assess the feasibility of thoseoptions, an assumption, this approach can be put into thecommon context of the MDMP as depicted in Figure 4:Task Based Planning and Automation of the MDMP.Figure 4: Task Based Planning and Automation of theMDMPThe tactical graphics represented by the sketch apply toone or more AUTL tasks. Each AUTL task represents auniversal standard set of measures across MTPs. Thismeans one or more MTP mission task sets are related toeach AUTL task. The appropriate MTPs are selectedbased on the functional type of unit as specified by theunit icon (type and echelon) on the sketch.The selection of AUTL tasks based on the tactical graphicenables the identification of options at the mission level.Each AUTL task then maps to one or more mission tasksets by unit type and echelon. The set of options arefurther scoped by the identification of the tactical graphic.Individual options are generated by identifying the AUTLtask(s), unit type & echelon, and then the MTP missiontask sets. The total set of options encompasses the“Options Envelop” for planning. This envelop expandsupon an N2 paradigm of options. Candidate options areselected based on the criteria (designated measures) andconstraints which are the factors of mission, enemy,troops, terrain, and time constraints (METT-TC). Thesediscriminators are used to differentiate measures intogroups of MOPs and MOEs for use by COA Generatorand COA Analyzer.1.5Sketch the PlanGraphics entered in a COA sketch represent higherheadquarters (HHQ) inputs to the task based approach toplanning. This means the task based approach to planningis used to evaluate options for the subordinate elements toachieve their HHQ objectives as represented by the sketch(commander’s intent).In this phase of planning the commander’s sketch istranslated into 2525B graphics. These graphics are thenused to identify the applicable AUTL tasks.1.6Army Universal Task ListThe AUTL tasks provide a common framework ofmeasures used to first assess the feasibility of a COA, andsecond to compare COA options leading to the selectionof the COA that best answers the higher ion,synchronization, etc). However, the AUTL does notprovide sufficient detail to enable these processes tosucceed. The AUTL does not place the task in context ofthe steps to be performed, the type of unit that willconduct the task, nor does it place the measures intocontext of the task’s performance. These requirementsare provided for by Mission Training Plans that arespecific to the unit type/size conducting the task. TheAUTL can be used to identify the MTP missions/taskswhich apply as well as the AUTL task(s) which proceedand follow each any AUTL task (horizontal planning).Therefore the AUTL is used in conjunction with the COAsketch to identify options in terms of the types of units tobe used for a COA, and the mission task sets those unitswill perform.1.7COA Generator, the MTP Tasks and COAAnalysisMTP tasks place AUTL tasks into context of the element(unit) that is being tasked. The AUTL tasks are used inconjunction with MTP tasks to: Identify which MTPs apply to the AUTL,representing options of which types of units canaccomplish the COA (mission) represented by thesketch. Identify options which are a list of MTP missions(task sets), specific to each type of unit, representingthe combination of one or more MTP tasks. Specify the effective measures (criteria) that apply toeach MTP task, in specific context to the situationrelated to the graphics (sketch).These criteria are then placed in specific context of theMETT-TC situation that is provided for in the COAsketch using a method of evaluation to generate a value ormeasure of effectiveness. The combination of thesefactors provides the MOE values for each MTP task in aCOA specific context.MOE MethodofEvaluation(METT-TC, Criteria, MOPs)Those performance measures of the MTP task designatedas critical (*) represent the basis for identifying thecommander’s critical information requirements (CCIR).
Those measures designated as leader ( ) representpotential decision points (DP) for the COA.The COA Generator then estimates the measures ofperformance for each performance measure. These MOPestimates are then used by methods of evaluation toestimate the MOE. Given these MOPs and MOEs for eachoption, the COA Analyzer can assess the tasks, steps, andperformance measures based on the measures ofeffectiveness and task criticality.1.8COA Analyzer and COA SelectionBecause an AUTL task has a single set of measures, thesemeasures can be used as common criteria (selectioncriteria), and task specific MOP values which representthe inputs to the weighting scheme used to compare therelative values of COA options. The weighting scheme isrepresented by the doctrinal rollup of Go-NoGo measuresof performance for each MTP task resulting in a TPUrating, where T Totally Effective, P Partially Effective,and U Un-effective.1.9Situational DevelopmentAs a COA executes (develops), the METT-TC situationchanges.These changes enable a more informedselection or development of a COA for the next phase ofexecution given the previously identified set of CandidateCOAs.1.10Task Hierarchy and Backwards PlanningTasks are by nature hierarchical. Each step of a task isrepresentative of a task (sub-task) in and of itself. Thissub-task may be defined in the same task document(MTP), or in another collective task document. Abattalion task consisted of commander/leader tasks(decision points) as well as aggregations of subordinatetasks. The top of the hierarchy is the AUTL. The AUTLspecifies the measures that apply to all lower MTP tasks.These MTP tasks place each AUTL task in specificcontext to the type and size of the element (unit)performing the task. The MTP also places the measuresin specific context to the performance (steps) of the task.Consider a battalion level task as representing a missionor phase of a mission to the battalion’s subordinateelements. The objective and designate measures (criteria)of the battalion task constrains the options for howsubordinate elements will perform their tasks. It specifiesthe criteria for evaluating MOE values of the tasks. Thesecriteria of a HHQ task’s objectives represent the effectivefuture for a subordinate’s performance. The top-downdecomposition of tasks is the basis for backwards, or topdown planning.Each MTP task identifies the unit’s element to which itapplies. So, an Infantry Battalion MTP will identify whichtasks apply to each class/type of subordinate element(HHC, Infantry Company, FA Battery, etc). So the MTPtasks decompose vertically down to the subordinateelements of the unit.1.11Task SequenceThe AUTL does more than identify measures of universalArmy tasks. It also identifies the situational context forwhen the task is to be performed, and the tasks to follow.The identification of the tasks to follow provides theknowledge of why a task is to be performed. For exampleconduct tactical road march is performed to relocate a unitto an area of operations. If the unit is already in thecorrect area, that task can be eliminated (dropped) fromconsideration for an option or branch. So, AUTL can beused to propose follow on tasks as subsequent courses ofaction.2Systems ViewThe systems view identifies connectivity and informationflow between components of a system.Here weinvestigate this view from two contexts. First we examinethe inter-connections between the task based planner andother components of the system. Second, we examine theintra-connections within the task based planner.2.1Inter-ConnectivityThe Inter-Connectivity system view identifies the logicalconnections between the task based planner and othersystem components.Figure 5: Systems Inter-Connectivity View Computer Generated Forces (CGF) – In this context,CGF is used to indicate a near-fully automated SAFthat includes intelligent Agents that provide forautomated command and control over a SAF. Theseagents effectively model/simulate a military roleplayer.
Agents – Intelligent C2 Agents are used to commandand control the SAF.These agents interpretmeasures (criteria) from the orders (MSDL/BML) tocompute MOP values as inputs to SAF orders. Asthe situation develops these agents re-compute theinputs as necessary to ensure the SAF performseffectively. When C2 over SAF performance is noteffective, the Agent then raises alerts as situationalreports to the operator so the COA (task/order) canbe re-planned accordingly. For example, if a unit isunable to reach a coordination point in time, the planwill need to be resynchronized. Semi-Automated Forces (SAF) – SAF systems areperformance based. They execute tasks based onvariables that don’t cross-correlate in context tomeasures of an order. SAF systems don’t performtradeoffs between measures; trade off speed forsecurity for example. So a for a traveling order, aSAF would take inputs of a route, and travelingspeed, rather than a start point, end point, level ofsecurity, and times to begin and end the travel.Stated in another way, SAF orders require theoperator to specify the specific means foraccomplishing the mission. By constraining themeans we constrain flexibility of the SAF whichmitigates cross-correlation between measures of thetask. The flexibility of C2 is applied to Agents, notthe SAF. Just as a driver provides for C2 over theperformance of a vehicle. Military Scenario Definition Language (MSDL) –MSDL is used to capture the plan coming out of theTask Based Planner as input to the CGF and otheroperational components of command and control. BML – BML is used to publish and subscribe tosituational and COA developments/updates. JC3IEDM – JC3IEDM provides the logical datamodel for persisting MSDL and BML details e Intra-Connectivity system view identifies the logicalconnections between internal components of the taskbased planner. This systems connectivity view focuses ondata flow and the inter-dependencies of the data that driveuse case dependencies. This view does not reflect anactual use case. In particular the feedback loop of replanning as the situation develops is not represented.Figure 6: Systems Intra-Connectivity View(1) Sketched tactical graphics representing controlmeasures and unit icons (disposition) are entered by thecommander.(2) MIL STD 2525B symbology are derived by theplanning agent based on the commander’s sketch.(3) The commander constrains the selection/derivation of2525B tactical symbology.(4) The resulting tactical graphics and unit icons areproduced in a known METT-TC context. The METT-TCcontext is represented by time frame, disposition oftroops, and disposition of threats.(5) The COA Generator uses the tactical graphics (verbs)to identify candidate AUTL tasks. The AUTL tasksprovide common criteria (measures) that apply across unitdoctrine (MTP tasks).(6) The COA Generator uses the unit icons to scopecandidate MTP task sets. These represent the completeset of MTP tasks that apply to the unit type/size.(7) AUTL tasks and measures are used to selectcandidate MTP tasks (options) from the candidate MTPtask sets.(8) Selected candidate MTP tasks and AUTL measuresare used by the COA Generator to generate proposedCOA options in the specified METT-TC context.(9) Proposed COA options are output in MSDL foranalysis. These COA options represent the OptionsEnvelop to be trimmed through computational analysis asthe METT-TC situation develops. The tasks are capturedin MSDL using constructs of C-BML grammar.(10) Candidate COAs, those that are feasible in thecurrent context, are output in MSDL.(11) As the situation develops (current context), candidateCOAs are trimmed from the options. This re-planningloop is not limited to the COA Analyzer. The loopinvolves additional iterations over all ten steps of theprocess.
2.3Sketch the PlanSketch the Plan takes the commander’s inputs as a sketchand outputs 2525B graphics and task organizationelements (unit icons). The results are output to the COAGenerator in MSDL format. This MSDL scenario wouldinitially include aggregate units, tactical graphics andoverlays, and other METT-TC situational details. In a replanning mode, the MSDL scenario may includecandidate COAs in addition to the situational scope.2.4COA GeneratorThe COA Generator identifies candidate AUTL tasks thatapply to each tactical graphic. The COA Generatorinteracts with the Planning Agent to further constrainoptions by trimming the set of AUTL tasks, and candidateMTP task sets (units to perform the task). As the plandevelops, specific units are allocated to the array of uniticons.The designation of these units includesidentification of their METL. The identification of theMETL further constrains COA options provided withinthe MTP task sets.2.5AgentsAutomated
of a task’s performance being effective in context to a mission or COA. 1.3 Operational Task Based Planning The Task Based concept is an innovative approach to using the Army’s Universal Task List (AUTL) to support the assessment and decision making of ongoing military operations while they are being conducted. The approach
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