suo/pda arpi fall 1999 workshop 1arpi small unit operations suo/pda austin tate & david wilkins...
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SUO/PDAARPI Fall 1999 Workshop 1
ARPIARPISmall Unit Operations SUO/PDA
Austin Tate & David WilkinsAIAI & SRI InternationalE-mail: [email protected], [email protected]: http://www.aiai.ed.ac.uk/~arpi/SUO/
SUO/PDAARPI Fall 1999 Workshop 2
ARPIARPISmall Unit Operations SUO/PDA
Advanced Planning Technology Schedule
SUO/PDA Objective
Demonstrate capability relevant to a SUO/Situation Assessment System (SAS) environment to generate, refine, select, communicate, execute and repair plans across multiple echelons.
Limited interfaces available on soldier-borne device.
Two examples of COA plan generation and use:- Defensive - Halt an Attack in Restrictive Terrain;- Offensive - Military Operations in Urban Terrain.
2QCY99 - SUO Scenario and storyboard/demo script development. Walk-through of technical requirements, mockup of non-working parts. Produce demo script and scenarios.
3QCY99 - Technology and demonstration development first pass, interim demonstration.
4QCY99 & Q1CY00 - Full demonstration development.
1Q & Q2CY00 - Transition and communication of results to SUO contractor. Refinement of demonstration and technology.
• Use results of DARPA/AFRL Planning Initiative (ARPI) and Planning & Decision Aids (PDA) work
• Multi-Agent Planning Architecture (MPA) and O-Plan Systems Integration Architecture
• SIPE-2/CPEF and O-Plan AI Planners• Mixed Initiative Planning Aids• Planning Domain Knowledge Acquisition Tools/Editors• Continuous Planning, Re-planning and Plan Repair• Planning Process Panels• Rich Shared Plan Representations
SUO/PDAARPI Fall 1999 Workshop 3
ARPIARPIObjective
• Demonstrate capability relevant to a SUO/Situation Assessment System (SAS) environment to generate, refine, communicate, execute and repair plans across multiple echelons.
• Limited interfaces available on soldier-borne device.
• Two examples of COA plan generation and use:
• Defensive - Halt an Attack in Restrictive Terrain;
• Offensive - Military Operations in Urban Terrain.
SUO/PDAARPI Fall 1999 Workshop 4
ARPIARPIApproach
• Use results of DARPA/AFRL Planning Initiative (ARPI) and Planning & Decision Aids (PDA) work
• Multi-Agent Planning Architecture (MPA) and O-Plan Systems Integration Architecture
• SIPE-2/CPEF and O-Plan AI Planners• Mixed Initiative Planning Aids• Planning Domain Knowledge Acquisition Tools/Editors• Continuous Planning, Re-planning and Plan Repair• Planning Process Panels• Rich Shared Plan Representations
SUO/PDAARPI Fall 1999 Workshop 5
ARPIARPILong-term Contributions to the Soldier
• Fast generation of multiple distinct COAs, including ones the commander may not have considered.
• Commander can explore more options in detail.
• Avoid mistakes: uniformly high plan quality, even during high-stress crises.
• Monitor plan execution and respond quickly to events, helping the commander modify the plan appropriately.
• Provide relevant information to other echelons, allowing fast communication while preserving bandwidth.
SUO/PDAARPI Fall 1999 Workshop 6
ARPIARPIPractical Issues/Challenges
• Effort to acquire the knowledge base (KB). • KB will cover a small subset of an officer’s knowledge and will add value.• Effort commensurate with capability.• Reduce effort by limiting scenario, relying on human knowledge, etc.• Human can override PDA -- blind spots not fatal• Other DARPA programs address this problem in the larger scale
• Assumptions about the world information available from sensors.
• Rely only on information which the SUO/SAS can provide• Baseline: SALUTE reports and GPS data.
• Input and output burden on soldiers when using SUO/PDA.• PDA would augment officer at time he would consult map or talk on radio• Voice input and limited interface modalities being considered by SUO contractor.
• Sensor planning• PDA will plan for awareness requirements• PDA will respond to reports from SAS• Will not model low-level details of sensor operations, or plan their exact deployment
SUO/PDAARPI Fall 1999 Workshop 7
ARPIARPI
• Validate MPA by integrating several systems in DARPA Planning Initiative (TIE 97-1):
INSPECT (ISI) OPIS (CMU) Advisable Planner (SRI)
SIPE-2 (SRI) ACS (UMass) Process Panel (AIAI -UEdin)
APAT (ISX) VISAGE (MAYA)
• Domain is Air Campaign Planning
• thousands of objects, several thousand nodes in each plan
• plan down to support mission level (must allocate supporting resources)
• air superiority objective only
• targets grouped into networks which depend on other networks
• network effectiveness is modeled quantitatively
Integration/TIEs
SUO/PDAARPI Fall 1999 Workshop 8
ARPIARPITIE 97-1 Demonstrations
• Sept 98 - EFX 98, Ft. Walton Beach FL
• May 98 - ARPI Workshop, Monterey CA
• Feb 98 - DARPA, Arlington VA
• Dec 97 - JFACC PMR, San Pedro CA
• Nov 97 - ARPI Workshop, San Francisco CA
Inc r
eas i
n g C
apab
ilit
ies
DARPADARPA
SUO/PDAARPI Fall 1999 Workshop 9
ARPIARPITechnology Transition
DARPA SUO program:
-prototype planning and decision aid
DARPA JFACC program:
-building on Cypress, MPA, TIE 97-1 MAPVis
SUO/PDAARPI Fall 1999 Workshop 10
ARPIARPISUO Scenarios
• Two SUO-SAS scenarios have been chosen:• Military Operations in Urban Terrain (MOUT):
Operation San Roberto
• Halt an Attack in Restrictive Terrain:
Operation Golden Manacle
• KA has been performed for both scenarios
• Interim demo is in MOUT scenario
• Main demo is in Halt an Attack scenario
SUO/PDAARPI Fall 1999 Workshop 11
ARPIARPIDifferences between the Two Scenarios
Halt an Attack Defensive Restrictive wooded terrain Battalion-sized operation Wide area move planning Mechanized threat Wide area sensors BN, CO, PLT Workstation-based aids Graphics+typing modalities
MOUT Offensive Close confined urban terrain Company-sized operation Close combat Foot soldier threat Localized sensors CO, PLT, SQ Soldier-borne aids Glance+select modalities
SUO/PDAARPI Fall 1999 Workshop 12
ARPIARPI
Opportunities for PDA Support in MOUTOpportunities for PDA Support in MOUT
Overall Process from Receipt of Mission to Success
Deliberative Planning & Rehearsal
En-route Rehearsal & Replanning
Low Tempo Adaptation & Plan Repair
High Tempo Monitoring & Plan Selection
After Action Planning &
Support
In Advance During Mission After Action
SUO/PDAARPI Fall 1999 Workshop 13
ARPIARPI
MOUT Concept of Operations
1st Plt
2nd Plt
OP “M” 3rd Plt 4th Plt
SUO/PDAARPI Fall 1999 Workshop 14
ARPIARPIHalt an Attack - Defensive Scenario
• Halt a mechanized enemy regiment in restrictive terrain with a SUO battalion
• Place obstacles to force enemy into engagement area
• Use forward infantry to observe, channel, and delay
• Rely on fire support to attrit
• Channel enemy to Southwest
• Use a CO(+) to defeat enemy in engagement area
SUO/PDAARPI Fall 1999 Workshop 15
ARPIARPIDefensive Scenario - Plan Generation
• BN plan/order is input to PDA
• PDA produces plans for each CO and each PLT
• KB covers following:• Observing avenues of approach (AAs)
• Using sensors to provide and supplement observation and to provide security
• Covering AAs with obstacles
• Positioning units
• Selecting a channelizing path for OPFOR
• Nominating positions for fire support (FS) units
• Selecting an engagement area (EA) in which to defeat channelized units
• Preparing the EA for the battle
SUO/PDAARPI Fall 1999 Workshop 16
ARPIARPIMain Demo - Halt an Attack
CompanyPlanning &Execution
System
OPORDFRAGO
PlatoonExecutionSupportSystem
OPORDFRAGO
BattalionPlanning &Execution
System
Reports
Reports
Domain ModelActivity
Templates &Constraints
Initial BattalionOPORD Creation
and Editing
Control PanelUser Interfaces& C2 ProcessManagement
World Simulationand Scenario
Event Generation
SUO/SAS System
World Simulator
AIAI Responsibility
SRI Responsibility
SUO/PDAARPI Fall 1999 Workshop 17
ARPIARPISUO/PDA Knowledge Acquisition Stage
Process ModellingMethods& Tools
Knowledge Acquisition for Halt an Attack(SRI with AIAI)
Army CALL BulletinsDoctrine, SOP, TTP
Subject Matter Experts
Domain ModelActivity
Templates &Constraints
SIPE Acts
O-Plan TF
SUO 3 Repn.Knowledge Acquisition for
MOUT(AIAI with SRI)
AIAI Responsibility
SRI Responsibility
SUO/PDAARPI Fall 1999 Workshop 18
ARPIARPIAIAI Contributing Technology
Austin Tatewith Jeff Dalton, John Levine, Peter JarvisAIAI, University of Edinburgh80 South Bridge, Edinburgh, UKE-mail: [email protected]: +44 (131) 650 2732
www:http://www.aiai.ed.ac.uk/project/oplan http://www.aiai.ed.ac.uk/project/ix
SUO/PDAARPI Fall 1999 Workshop 19
ARPIARPIAIAI Contributing Technology
• Generation of multiple qualitatively distinct alternative COAs dependent upon alternative assumptions and advice about the situation.
• Support for mixed-initiative incremental plan development, manipulation and use.
• Situation-dependant plan repair as situation changes.
• Systems integration framework for modular planning and plan analysis systems.
• Management of planning and execution process - promotion of intelligent process management and workflow concepts.
SUO/PDAARPI Fall 1999 Workshop 20
ARPIARPIAIAI Contributing Technology
• Shared Models of Tasks, Processes and Plans
• Issue-based Problem Solving
• Constraint and Domain Management
• Planning Process Panels
• Web Delivery of Planning Facilities
• Process Editor
• Previous O-Plan Technology
• New I-X Technology
SUO/PDAARPI Fall 1999 Workshop 21
ARPIARPI
Shared Plan Model - a rich plan representation using
a common constraint model of activity (<I-N-CA>).
Shared Task Model - Mixed initiative model of
“mutually constraining the space of behaviour”.
Shared Space of Options - explicit option management.
Shared Model of Agent Capabilities - handlers for
issues, functional capabilities and constraint managers.
Shared Understanding of Authority - management
of the authority to plan (to handle issues) and
act which may take into account options,
phases and levels.
SUO/PDAARPI Fall 1999 Workshop 22
ARPIARPIO-Plan -> I-X
InterfaceManager
ControllerProcessingPlatform(s)
Data Base Manager
Plan State Issues Nodes Constraints
ConstraintAssociator
Issue Handlers
Information Sources
Constraint ManagersPlanWorldViewers
RequirementsRequirements
Reports Reports
Constraint Managers
Processing Capabilities
Technical & World Viewers
Task & OptionManagement
ModelManagement
Mediators/MappingInformation Sources
RequirementsRequirements
Reports Reports
SUO/PDAARPI Fall 1999 Workshop 23
ARPIARPII-Plan and <I-N-CA>
Plan Agenda
Plan Entities
Plan Constraints
Plan State
Space of Legitimate Plan Elaborations
Choose (IH)
Do (IH)
IH=Issue Handler (Agent Functional Capability)
PropagateConstraints
Issues or ImpliedConstraints
NodeConstraints
DetailedConstraints
I
N
CA
C=Critical ConstraintsA=Auxiliary Constraints
SUO/PDAARPI Fall 1999 Workshop 24
ARPIARPISRI Contributing Technology
David Wilkins, Tom Lee SRI InternationalArtificial Intelligence CenterMenlo Park, CAE-mail: [email protected]: 650-859-2057
www: http://www.ai.sri.com/~sipe http://www.ai.sri.com/~cpef
SUO/PDAARPI Fall 1999 Workshop 25
ARPIARPI
Domain Characteristics
• Tasks are complex and open-ended
• Operating environments are dynamic and possibly hostile
• Complete and accurate knowledge of the world can never be attained
• Full automation is neither possible nor desirable Successful operation requires a mix of
• user involvement and control
• continuous planning
• rapid response to unexpected events
• dynamic adaptation of activities
Intelligent Operations Management
SUO/PDAARPI Fall 1999 Workshop 26
ARPIARPICPEF Architecture
Plan Manager
PRS
Planner
AP/SIPE
Simulator
PRS
Repair
Requests
Repair
Info
Plan
Requests
Plan Info
Situation
Updates
Execution
Status
Execution
Requests
Updates,
Guidance
Plan Server
PRS
Interface
PRS
Plan Repair
PRS
Notifications,
Requests
Plans
PlansPlans
MPA Messages